Patent Description:
Data security and user privacy are vital in systems and devices connected to public networks, such as the Internet. The enhancement of user privacy has led many developers to change the ways in which user data is handled. For example, some browsers are planning to deprecate the use of third-party cookies.

<CIT> discloses a content provider that has a single relation to a central operator which in turn has relations to other operators. The content provider reaches all users of all operators through a single relation to that operator. The content provider provides service content, e.g. media content. A list of targeted users or subscribers is compiled. The central operation collects necessary subscriber attributes such as position, device information and access properties, from the other operators. The content is modified according to the collected attributes, and the content is distributed to the subscribers.

<CIT> discloses a mobile network device that creates and continuously modifies an anonymous user profile from collected network data and subsequently shares the profile with content providers. The mobile network device includes multiple collector devices that monitor data from routers on the mobile data network for application-level activity and a corresponding IP address or mobile phone number. The collectors then analyze the content involved with the activity and correlate it to an IP-address-phone-number pair to create a user profile. Each collector then modifies the user profile with the user's location information at the time the activity was requested. Each collector subsequently transforms the user profile into an anonymous user profile vector and shares it with the profile manager. By repeating this process over time, the collectors create and modify an anonymous user profile vector that can be shared with content providers for targeted advertising.

This specification describes methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for generating and processing non-identifying user data to select and provide digital content to client devices in a privacy-preserving manner.

In one innovative aspect, this specification describes a method for distributing digital components to client devices. The method can be implemented by a system including one or more computers.

For each of a plurality of client devices, the system receives a digital component request from an application running on the client device of a user. The system identifies, based on the digital component request, one or more user attributes of the user. The system sends, to the application, a digital component response including (i) one or more digital components and (ii) attribute data comprising the one or more user attributes of the user, wherein the application is configured to update, based on the one or more user attributes, accumulated user attribute data stored in a shared storage of the client device in response to receiving the attribute data. The system obtains, from the shared storage of each of the plurality of client devices, the accumulated user attribute data stored in the shared storage of each client device. The system generates an aggregated user attribute report for one or more aggregation keys using the obtained accumulated user attribute data, including, for each of the one or more aggregation keys, obtaining an aggregated data profile that is generated by aggregating the accumulated user attribute data from a subset of the client devices that have accessed an electronic resource or a digital component identified by the aggregation key. The system adjusts, based on the aggregated data profiles, one or more distribution parameters for distributing digital components to client devices in response to digital component requests. The system distributes digital components to the client devices based on the distribution parameters. Other implementations of this aspect include corresponding apparatus, systems, and computer programs, configured to perform the aspects of the methods, encoded on computer storage devices.

These and other implementations can each optionally include one or more of the following features. In some implementations, to generate the aggregated user attribute report, the system sends, to a secure aggregation system, an aggregation request including the accumulated user attribute data obtained from each of the client devices and the one or more aggregation keys, and receives, from the secure aggregation system, the aggregated data profile generated in response to the aggregation request. The accumulated user attribute data received from each client device can be encrypted by the client device using an encryption key of the secure aggregation system.

In some implementations, the digital component request includes contextual data related to an environment in which the one or more digital components will be displayed at the client device. The environment can include an electronic resource and the contextual data can include a resource locator for an electronic resource in which the one or more digital components will be displayed at the client device, and/or topics of content of the electronic resource.

In some implementations, the one or more user attributes are identified using a predictive model configured to predict attributes of users that have accessed the electronic resource or the topics of the contents of the electronic resource. The application can be configured to: in response to receiving the user attributes identified using the predictive model, determine whether the accumulated user attribute data stored in the shared storage of the client device includes a keyed entry for the one or more user attributes; in response to the accumulated user attribute data not including the keyed entry, generate a new keyed entry in the accumulated user attribute data, and assign an entry value for the new keyed entry based on the one or more user attributes identified using the predictive model; and in response to the accumulated user attribute data including the keyed entry, update a current entry value of the keyed entry in the accumulated user attribute data based on the one or more user attributes identified using the predictive model. To update the current entry value of the keyed entry, the application can be configured to increment or decrement the current entry value of the keyed entry in response to the accumulated user attribute data including the keyed entry.

In some implementations, the user is subscribed to the electronic resource with a user identifier, and the one or more user attributes are identified using a user profile associated with the user identifier. The application can be configured to: in response to receiving the user attributes identified using the user profile, determine whether the accumulated user attribute data stored in the shared storage of the client device includes a keyed entry for the one or more user attributes; in response to the aggregated user attribute data not including the keyed entry, generate a new keyed entry in the accumulated user attribute data, and assign an entry value for the new keyed entry based on the one or more user attributes identified using the user profile; and in response to the accumulated user attribute data including the keyed entry, update the entry value of the keyed entry in the accumulated user attribute data based on the one or more user attributes identified using the user profile. A user interface of the electronic resource can include a code to cause the application to update the accumulated user attribute data based on the one or more user attributes in response to receiving the user attributes.

In some implementations, the aggregated profile for an aggregation key includes one or more metrics for the electronic resource or the digital component identified by the aggregation key. The one or more metrics can include a reach metric measuring a number of unique users in the subset of client devices that have accessed the electronic resource or the digital component identified by the aggregation key.

In some implementations, to aggregate the user attribute data from the subset of client devices, the system adds a random noise to the user attribute data of each of the subset of client devices before aggregating.

A content distribution system can leverage user attribute data of a set of users, e.g., users that have accessed a particular electronic resource (e.g., website) or a digital component (e.g., a video/audio clip, image, or text) to guide the selection and distribution of content to other users, e.g., to distribute content that best fit the interests or needs of the users.

Historically, third-party cookies (e.g., cookies from a different domain than the resource being rendered by a client device) have been used to collect data from client devices across the Internet. For example, a third-party cookie can be a script file from a website other than the one the client device is currently visiting, typically for the purpose of tracking user behavior and/or serving digital content to the user. Due to the increasing concerns over user privacy and data protection, some browsers and device platforms block the use of third-party cookies and third-party cookies are increasingly being removed from use, thereby preventing the collection of data using third-party cookies. This creates a challenge when attempting to utilize collected data to enhance online browsing experiences, e.g., by selecting content relevant to users based on the data collected using third-party cookies. In other words, without the use of third-party cookies, much of the data previously collected is no longer available, which prevents computing systems from being able to use that data to predict interests or attributes of users based on activities performed by the users at particular web pages or other resources, to enhance the online experience for users, and/or to present relevant content to users.

The techniques described herein can solve hurdles that may arise from the eradication of third-party cookies. In particular, this specification describes techniques for obtaining privacy-preserving user attribute data from a shared storage of client devices. The shared storage of a client device maintains accumulated user attribute data characterizing attributes and/or interests of a user of the client device, and updates the accumulated user attribute data based on user attribute signals received from a content distribution system or a content-providing system. A computer system, e.g., a secure server, can collect the accumulative user attribute data from the client device without using third-party cookies. The computer system can generate an aggregated user attribute report from the user attribute data, and the content distribution system can use the aggregated user attribute report to guide the distribution of digital components.

By using these techniques, the content distribution system can effectively leverage user attribute data of a group of users to guide the selection and distribution of content to particular users without using third-party cookies. Instead of using third-party cookies, the described techniques for maintaining and utilizing privacy-preserving user attribute data using a shared storage of client devices. The shared storage provides a framework that enable sharing data across multiple sessions and/or multiple instances of accessing an electronic resource, e.g., a website, and/or sharing data across different electronic resources. The shared storage can also be implemented with measures to protect the security and privacy of the stored data. These techniques also provide user privacy protection for the process of collecting the user attribute data by preventing collecting and using sensitive information (e.g., personally identifiable information) of the user without the user's consent.

In general, this specification describes systems and techniques for providing digital content, e.g., digital components, to client devices in ways that protect user privacy. A server can be configured to obtain accumulated user attribute data from client devices and generate an aggregated user attribute report using the obtained user attribute data. A digital component distribution system can use the aggregated user attribute report to adjust distribution parameters for distributing digital components to client devices in response to digital component requests.

Further to the descriptions throughout this document, a user may be provided with controls (e.g., user interface elements with which a user can interact) allowing the user to make an election as to both if and when systems, programs, or features described herein may enable the collection of user information (e.g., information about a user's social network, social actions, or activities, profession, a user's preferences, or a user's current location), and if the user is sent content or communications from a server. In addition, certain data may be treated in one or more ways before it is stored or used, so that personally identifiable information is removed. For example, a user's identity may be treated so that no personally identifiable information can be determined for the user, or a user's geographic location may be generalized where location information is obtained (such as to a city, ZIP code, or state level), so that a particular location of a user cannot be determined. Thus, the user may have control over what information is collected about the user, how that information is used, and what information is provided to the user.

<FIG> is a block diagram of an example environment <NUM> in which a digital component distribution system <NUM> distributes digital components to client devices <NUM>. The environment <NUM> includes a data communication network <NUM>, such as a local area network (LAN), a wide area network (WAN), the Internet, a mobile network, or a combination thereof. The data communication network <NUM> connects client devices <NUM> to the digital component distribution system <NUM>. The network <NUM> can also connect the digital component distribution system <NUM> digital component providers, e.g., <NUM>-<NUM>, <NUM>-<NUM>, and <NUM>-<NUM>.

A website <NUM> is one or more electronic resources associated with a domain name and hosted by one or more servers. An example website is a collection of web pages formatted in HTML that can contain text, images, multimedia content, and programming elements, such as scripts. Each website <NUM> is maintained by a publisher <NUM>, which is an entity that controls, manages and/or owns the website <NUM>.

An electronic resource is also referred to herein as a resource for brevity. In this specification, resources can include HTML pages, word processing documents, and portable document format (PDF) documents, images, video, and feed sources, to name only a few. The resources can include content, such as words, phrases, images and sounds, that may include embedded information (such as meta-information in hyperlinks) and/or embedded instructions (such as scripts). A resource can be identified by a resource address, e.g., a Universal Resource Locator (URL) that is associated with the resource.

A client device <NUM> is an electronic device that is capable of communicating over the network <NUM>. Example client devices <NUM> include personal computers, server computers, mobile communication devices, e.g., smart phones and/or tablet computers, and other devices that can send and receive data over the network <NUM>. A client device can also include a digital assistant device that accepts audio input through a microphone and outputs audio output through speakers. The digital assistant can be placed into listen mode (e.g., ready to accept audio input) when the digital assistant detects a "hotword" or "hotphrase" that activates the microphone to accept audio input. The digital assistant device can also include a camera and/or display to capture images and visually present information. The digital assistant can be implemented in different forms of hardware devices including, a wearable device (e.g., a watch or a pair of glasses), a smart phone, a speaker device, a tablet device, or another hardware device. A client device can also include a digital media device, e.g., a streaming device that plugs into a television or other display to stream videos to the television, a gaming device, or a virtual reality system.

A gaming device is a device that enables a user to engage in gaming applications, for example, in which the user has control over one or more characters, avatars, or other rendered content presented in the gaming application. A gaming device typically includes a computer processor, a memory device, and a controller interface (either physical or visually rendered) that enables user control over content rendered by the gaming application. The gaming device can store and execute the gaming application locally, or execute a gaming application that is at least partly stored and/or served by a cloud server (e.g., online gaming applications). Similarly, the gaming device can interface with a gaming server that executes the gaming application and "streams" the gaming application to the gaming device. The gaming device may be a tablet device, mobile telecommunications device, a computer, or another device that performs other functions beyond executing the gaming application.

A client device <NUM> can include applications <NUM>, such as web browsers and/or native applications, to facilitate the sending and receiving of data over the network <NUM>. A native application is an application developed for a particular platform or a particular device (e.g., mobile devices having a particular operating system). Although operations may be described as being performed by the client device <NUM>, such operations may be performed by an application <NUM> running on the client device <NUM>.

The applications <NUM> can present electronic resources, e.g., web pages, application pages, or other application content, to a user of the client device <NUM>. The electronic resources can include digital component slots for presenting digital components with the content of the electronic resources. A digital component slot is an area of an electronic resource (e.g., web page or application page) for displaying a digital component. A digital component slot can also refer to a portion of an audio and/or video stream (which is another example of an electronic resource) for playing a digital component.

As used throughout this specification, the "digital component" refers to a discrete unit of digital content or digital information (e.g., a video clip, audio clip, multimedia clip, image, text, or another unit of content). A digital component can electronically be stored in a physical memory device as a single file or in a collection of files, and digital components can take the form of video files, audio files, multimedia files, image files, or text files and include advertising information, such that an advertisement is a type of digital component. For example, the digital component may be content that is intended to supplement the content of a web page or other resource presented by the application <NUM>. More specifically, the digital component may include digital content that is relevant to the resource content (e.g., the digital component may relate to the same topic as the web page content, or to a related topic). The provision of digital components can thus supplement, and generally enhance, the web page or application content.

When the application <NUM> loads a resource that includes a digital component slot, the application <NUM> can generate a digital component request that requests a digital component for display in the digital component slot. In some implementations, the digital component slot and/or the resource can include code (e.g., scripts) that cause the application <NUM> to request a digital component from the digital component distribution system <NUM>.

A digital component request can include contextual data, which is generally considered non-sensitive. The contextual data can describe the environment in which a selected digital component will be presented. The contextual data can include, for example, coarse location information indicating a general location of the client device <NUM> that sent the digital component request, a resource (e.g., website or native application) with which the selected digital component will be presented (e.g., by including a resource locator such as a URI or URL for the resource), a spoken language setting of the application <NUM> or client device <NUM>, the number of digital component slots in which digital components will be presented with the resource, the types of digital component slots, and/or other appropriate contextual information.

As described in more detail below, the digital component distribution system <NUM> can identify, e.g., predict, user attributes of the user of the client device <NUM> from which a digital component request is received based on data (e.g., contextual data) included in the digital component request. In response to the digital component response, the digital component distribution system <NUM> can send attribute data specifying the user attributes identified from the digital component request to the client device <NUM>.

The application <NUM> maintains a shared storage <NUM> that stores a set of data that can be accessed and updated by the application <NUM>. The data stored in the shared storage <NUM> can have any appropriate data formats according to specific applications, preferences, and/or or protocols. The data stored in the shared storage <NUM> can be shared across multiple sessions and/or multiple instances of the application <NUM>. For example, the stored data can be shared by all instances of an electronic resource (e.g., a website) running in different tabs or windows of the application <NUM>. In some implementations, the data stored in the in the shared storage <NUM> can be shared across multiple electronic resources, e.g., multiple websites that have been accessed by the application.

Several measures can be taken to protect the security and privacy of the data stored in the shared storage <NUM>. For example, in some implementations, the shared storage <NUM> can be in a separate portion of the storage space of the application <NUM>. In some implementations, a separate thread of the application <NUM> manages and provides access to the shared storage <NUM>. The separate thread can isolate the shared storage <NUM> from being accessed by other components of the application <NUM>, and/or being accessed by unauthorized websites, e.g., websites that the user has not interacted with. In some implementations, the application can encrypt the data stored in the shared storage <NUM> before transmitting the data to another system over the network <NUM>.

To provide data in guiding the selection and distribution of contents to users, the data stored in the shared storage <NUM> can include accumulated user attribute data characterizing a user of the client device <NUM>. The accumulated user attribute data can include data characterizing the interests of the user (e.g., topics of interest or hobbies) and/or data characterizing non-identifying demographic attributes of the user. As described in more detail below, the application <NUM>, e.g., the separate thread of the application <NUM>, is configured to update the accumulated user attribute data based on attribute data received from the digital component distribution system <NUM>.

The secure aggregation and reporting system <NUM> is configured to receive the accumulated user attribute data from the shared storage <NUM> of multiple client devices <NUM>, and use the accumulated user attribute data to generate an aggregated user attribute report for a set of aggregation keys. The system <NUM> can be a secure server implemented using one or more computers (or other appropriate computing devices), that may be distributed across multiple locations. The secure system <NUM> can be operated and maintained by the digital component distribution system <NUM> or an independent trusted party, e.g., a party that is different from the users of the client devices, the parties that operate the digital component distribution system <NUM>, and the digital component providers <NUM>. For example, the secure system <NUM> can be operated by an industry group or a governmental group.

In some implementations, the secure system <NUM> implements a secure environment, i.e., the shared storage worklet <NUM>, configured to access the shared storage <NUM> of the client devices <NUM> to receive the accumulated user attribute data, and process the accumulated user attribute data to generate the aggregated report. To provide additional security and privacy protection of user data, the shared storage worklet <NUM> can be a dedicated process or thread running on the secure system <NUM> that is separated from the other processes or threads of the secure system <NUM>.

The shared storage worklet <NUM> includes an aggregation key selection engine <NUM> and a data aggregation engine <NUM>. The aggregation key selection engine <NUM> is configured to select an aggregation key from a list of aggregation keys, and the data aggregation engine <NUM> is configured to generate an aggregated data profile by aggregating the accumulated user attribute data from a subset of the plurality of client devices that have accessed an electronic resource or a digital component identified by the aggregation key.

The digital component distribution system <NUM> can identify a set of digital components that are eligible to be presented to the client device <NUM> from among a corpus of digital components that are available from the content platform <NUM>. For example, the digital component distribution system <NUM> can select one or more digital components from digital components stored in a digital component repository and/or a set of digital components received from digital component providers <NUM>.

The digital component repository can store digital components received from the digital component providers and additional data (e.g., metadata) for each digital component in a database. The metadata for a digital component can include, for example, distribution criteria that define the situations in which the digital component is eligible to be provided to a client device <NUM> in response to a digital component request received from the client device <NUM> and/or a selection parameter that indicates an amount that will be provided to the publisher if the digital component is displayed with a resource of the publisher and/or interacted with by a user when presented. The distribution criteria and the selection parameter can be characterized by one or more distribution parameters.

For example, the distribution parameters for a particular digital component can include distribution keywords that must be matched, e.g., by terms specified in the request, in order for the digital component to be eligible for presentation. In another example, the distribution criteria for a digital component can include location information indicating which geographic locations that digital component is eligible to be presented, user group membership data identifying user groups to which the digital component is eligible to be presented, resource data identifying resources with which the electronic resource is eligible to be presented, and/or other appropriate distribution criteria. The distribution criteria can also include negative criteria, e.g., criteria indicating situations in which the digital component is not eligible (e.g., with particular resources or in particular locations). The distribution parameters can also specify a selection parameter and/or budget for distributing the particular third-party content.

As described in more detail below, the distribution parameters for a digital component can be adjusted based on the aggregated user attribute report for the digital component. The digital component distribution system <NUM> can identify eligible digital components based on the distribution parameters and data included in the digital component request. The digital component distribution system <NUM> can then select a digital component from the eligible digital components and provide the selected digital component to the client device <NUM> for display to the user of the client device <NUM>.

<FIG> is a swim lane flow diagram of an example process <NUM> for distributing digital components for display at client devices. Operations of the process <NUM> can be implemented, for example, by a client device <NUM>, a secure aggregation and reporting system <NUM>, and a digital component distribution system <NUM>, one or more publishers <NUM>, and one or more websites <NUM>. Operations of the process <NUM> can also be implemented as instructions stored on computer-readable media, which may be non-transitory, and execution of the instructions by data processing apparatus can cause the data processing apparatus to perform the operations of the process <NUM>.

At <NUM>, the client device <NUM> sends a request for an electronic resource, e.g., a request for a webpage to the website <NUM>. The request can include the URL of the electronic resource. At <NUM>, the website <NUM> sends the requested electronic resource to the client device <NUM>.

After receiving the requested electronic resource and while loading the electronic resource, the client device <NUM> generates a digital component request that requests a digital component for display in a digital component slot of the electronic resource. The digital component request includes contextual data that describes the environment in which a selected digital component will be presented. For example, the contextual data can identify the electronic resource (e.g., the website) with which the selected digital component will be presented. In a particular example, the contextual data can include the URL or URI of the electronic resource. The contextual data can include, for example, coarse location information indicating a general location of the client device <NUM>, a spoken language setting of the client device <NUM>, the number of digital component slots in which digital components will be presented with the resource, the types of digital component slots, and/or other appropriate contextual information.

At <NUM>, the client device <NUM> sends the digital component request to the digital component distribution system <NUM>. The digital component distribution system <NUM> selects digital components based on the digital component request at 251a, and identifies one or more user attributes of the user based on the digital component request at 251b.

In some implementations, the digital component distribution system <NUM> identifies the user attributes using a predictive model (e.g., a trained machine learning model) based on the contextual data in the digital component request. For example, the predictive model can be configured to predict attributes of users that have accessed the electronic resource or the topics of the contents of the electronic resource. The digital component distribution system <NUM> can use the predictive model to process an input specifying the electronic resource and/or the topics of the contents of the electronic resource, and generate an output that includes a prediction of user attributes of the user, e.g., user interests (e.g., topics of interest) of the user, demographic attributes of the user, and/or other characteristics of a user that has accessed the electronic resource or the topics of the contents of the electronic resource. The user attributes and/or other characteristics predicted by the predictive model can be used to indicate attributes of the user of the client device <NUM>. In some implementations, the predicted model can further output a numerical value for a likelihood that the user has the predicted user attribute.

In some other implementations, when the user is signed in to the electronic resource with a user identifier, the digital component distribution system <NUM> can obtain, if permitted by the user, user attribute data associated with a user profile identified by the user identifier. For example, the user profile can specify or indicate user interests, demographic attributes, and/or other characteristics of the user. The digital component distribution system <NUM> can identify such information from the user profile.

At <NUM>, the digital component distribution system <NUM> sends a response to the client device <NUM>. The response includes the selected digital components and attribute data specifying the user attributes of the user, e.g., the user attributes identified based on the output of the predictive model and/or the user attributes identified based on the user profile.

In response to receiving the attribute data, at <NUM>, the client device <NUM> updates accumulated user attribute data stored in a shared storage of the client device <NUM> based on the user attributes specified by the attribute data.

In some implementations, when the user attributes have been identified using the predictive model based on the contextual data, the client device <NUM> can determine whether the accumulated user attribute data stored in the shared storage includes a keyed entry for an identified user attribute. If the accumulated user attribute data does not include the keyed entry, the client device <NUM> can generate a new keyed entry for the identified user attribute, and assign an entry value for the new keyed entry. On the other hand, if the accumulated user attribute data does include the keyed entry, the client device <NUM> can update a current entry value of the keyed entry based on the user attribute identified using the predictive model. For example, when updating the current entry value of the keyed entry, the client device <NUM> can increment or decrement the current entry value of the keyed entry.

In an illustrative example, a first digital component request received from the client device <NUM> can include contextual data that identifies a first electronic resource as "example. com//vegetablefertilizer/". The predictive model can output a prediction for a user accessing this webpage as being interested in gardening with a <NUM>% likelihood. The client device <NUM> can generate a keyed entry of "Interest in gardening" and assign a value of <NUM> to the entry. A second digital component request received from the client device <NUM> can include contextual data that identifies a second electronic resource as "example. com/gardendesign/". The predictive model can output a prediction for a user accessing this webpage as being interested in gardening with an <NUM>% likelihood. The client device <NUM> can update the value of keyed entry "Interest in gardening" by incrementing <NUM> to the value of the entry. The value of the keyed entry can be updated accumulatively based on the predicted user attributes related to the keyed entry.

In some other implementations, when the user attributes have been identified using the user profile data associated with the user identifier, the client device <NUM> can generate or update a keyed entry for one or more of the identified user attributes. For example, if the user profile data specifies or indicates that the user has an interest in gardening, the client device <NUM> can generate a keyed entry of "Interest in gardening" and assign a value of <NUM> to the entry. If the user profile data specifies or indicates that the user does not have an interest in gardening, the client device <NUM> can assign a value of <NUM> to the entry of "Interest in gardening".

In some implementations, when the electronic resource is being presented at the client device <NUM>, a user interface for presenting the electronic resource includes a script code that causes an application of the client device <NUM> to update the accumulated user attribute data based on the user attributes identified using the user profile.

At <NUM>, the secure aggregation and reporting system <NUM> obtains the accumulated user attribute data from the shared storage of the client device <NUM>. The processes described above, including <NUM>, <NUM>, <NUM>, 251a, 251b, <NUM>, and <NUM>, can be repeatedly performed for multiple client devices <NUM>, and the secure aggregation and reporting system <NUM> obtains the accumulated user attribute data from each of the multiple client devices <NUM>.

At <NUM>, the secure aggregation and reporting system <NUM> generates an aggregated user attribute report that includes a respective aggregated data profiles for each of a set of selected aggregation keys using the obtained accumulated user attribute data.

The system <NUM> can select an aggregation key based on contextual signals such as particular resource locators, particular digital components, particular geographic regions, and/or particular types of devices. For example, an aggregation key can be in the form of <URL, Region, Device Type>. In another example, an aggregation key can be in the form of <Digital component identifier, Region, Device Type>. Other appropriate signals can also be used. Aggregation keys can include a combination of contextual signals, topics, and/or other appropriate signals. In a particular example, an aggregation key can be <example. com/flowers, Canada, smartphone>. The aggregated profile for this key would include data related to a subset of users that have visited example. com/flowers from smartphones located in Canada.

The system <NUM> can select the aggregation key from a list of candidate aggregation keys. The list of candidate aggregation keys can be configured by various entities, such as the digital component distribution system <NUM> and/or a publisher <NUM> of digital content. The digital component distribution system <NUM> and/or a publisher <NUM> can provide, to the system <NUM>, configuration data that defines the list of candidate aggregation keys. The configuration data can also define, for each candidate aggregation key, the types of data to include in an aggregated profile for the aggregation key. For example, the configuration data can specify that the aggregated profile for a candidate aggregation key is to include, for each of multiple user attributes, a count of the number of users or a percentage of the users for which data is aggregated for the aggregation key that have that user attribute. Many combinations of data types can be included in an aggregated profile.

Once an aggregation key has been selected, the system <NUM> can identify the subset of client devices from which the accumulated user attributes will be used to generate the aggregated profile for the selected aggregation key. For example, the subset of client devices can be the client devices that have accessed the electronic resource or the digital component identified by the aggregation key. The selection of the subset of client devices can further be based on user permission settings. As noted above, for each client device, a user may be provided with controls (e.g., user interface elements with which a user can interact) allowing the user to make an election as to both if and when systems, programs, or features may enable the collection of user information and how such information is used.

In some implementations, before and/or during generating the aggregated profile using the accumulated user attribute data from the subset of client devices, the system <NUM> can apply privacy-preserving techniques to the accumulated user attribute data. These techniques can include anonymizing the data for each user, e.g., by removing any user identifiers from the data, applying k-anonymity techniques, and/or applying differential privacy techniques to the aggregated data.

For each selected aggregation key, the system <NUM> generates the aggregated profile by aggregating the accumulated user attribute data obtained from the identified subset of client devices. As noted above, an aggregated profile for an aggregation key can include various types of aggregated user data about users for which data is aggregated for the aggregation key. For example, the aggregated profile for an aggregation key can include a count of the number of users or a percentage of the users of the subset of client devices that have a particular attribute. In a particular example, the aggregated profile for the aggregation key <example. com/flowers, Canada, smartphone> can specify a percentage of the users of the identified subset of client devices that are female, a percentage of the users that have interests in the topic of gardening, and/or a percentage of the users that are English speakers.

In some implementations, the aggregated profile for an aggregation key can include a metric computed by the system <NUM>. For example, the aggregated profile can include a reach metric that characterizes the total number of unique users in a set of users who have accessed a particular electronic resource, or the total number of unique users to whom a particular digital component has been provided. In another example, the aggregated profile can include a frequency metric that characterizes the number of times a same user has been provided with a particular digital component. In another example, the aggregated profile can include an attribution metric that quantifies, for the subset of client devices that have been provided a particular digital component, the number of digital component impressions that have led to a specific action (e.g., a conversion), such as a user interaction with the provided digital component, a user sign-up, a purchase, etc..

At 224a, the system <NUM> sends the aggregated user attribute report to the digital component distribution system <NUM>. The system <NUM> can further send at least a portion the aggregated user attribute report to a publisher <NUM> or a website <NUM> (at 224b). For example, the system <NUM> can send the aggregated profile generated for a particular resource locator (e.g., a URL) to the corresponding website <NUM> or the publisher <NUM> of the resource.

At <NUM>, the digital component distribution system <NUM> can use the aggregated data profiles in the report to adjust distribution parameters for distributing digital components.

In an illustrative example, for an aggregation key specifying a particular resource locator, e.g., example. com/flowers, the aggregated profile can include a percentage of users that belong to a particular interest group, e.g., a group with a topic of interest "gardening". The distribution system <NUM> can determine whether the percentage of users exceed a predefined value, and in case the percentage does exceed the predefined value, the distribution system <NUM> can add a related interest group to the list of groups for the particular digital component or a related digital component to be eligible for presentation.

In some other examples, the distribution system <NUM> can adjust the distribution parameters based on the metrics included in the aggregated profiles in the report. In an illustrative example, when an aggregated data profile includes a reach metric for a particular digital component in a particular geographic region, the distribution system <NUM> can determine whether the reach metric exceeds a predefined threshold, and if the reach metric exceeds the predefined threshold, the distribution system <NUM> can determine to remove the particular geographic region from the list of geographic regions for the particular digital component or a related digital component to be provided. In another illustrative example, when the reach metric for the particular digital component exceeds a certain threshold and/or a frequency metric for the particular digital exceeds a certain threshold for users in a particular interest group, the distribution system <NUM> can determine to add a related interest group to the list of groups for the particular digital component or a related digital component to be eligible for presentation. In another illustrative example, when the reach metric for a particular digital component exceeds a certain threshold and/or the frequency metric for the particular digital component exceeds a certain threshold, the distribution system <NUM> can determine to increase or decrease the selection parameter and/or budget for distributing the particular digital component or a related digital component.

At <NUM>, the digital component distribution system <NUM> distributes digital components to the client devices <NUM> based on the distribution parameters. In particular, the distribution system <NUM> can select, according to the distribution parameters that have been adjusted at <NUM>, digital components for distribution to client devices <NUM> in response to receiving digital component requests from the client devices. The system <NUM> can then provide the digital components selected according to the updated distribution parameters to the client devices <NUM>. At <NUM>, the client device <NUM> can then present the provided digital component, e.g., by an application of the client device <NUM>.

<FIG> is a flow diagram of an example process <NUM> for distributing digital components for display at client devices. Operations of the process <NUM> can be performed by a system of one or more computers located in one or more locations, such as a server, e.g., the digital component distribution system <NUM> and/or the secure aggregation and reporting system <NUM> described with reference to <FIG>, appropriately programmed in accordance with this specification, can perform the process <NUM>. Operations of the process <NUM> can also be implemented as instructions stored on one or more computer-readable media, which may be non-transitory, and execution of the instructions by one or more data processing apparatus can cause the one or more data processing apparatus to perform the operations of the process <NUM>. For convenience and without loss of generality, the process <NUM> will be described as being performed by a data processing apparatus, e.g., a computer system.

At <NUM>, the data processing apparatus receives, for each of multiple client devices, a digital component request from an application running on the client device of a user. The digital component request can include contextual data related to an environment in which the digital components will be displayed at the client device. For example, the environment can include an electronic resource and the contextual data. The contextual data can include a resource locator (e.g., URL) for an electronic resource in which the one or more digital components will be displayed at the client device, and/or topics of content of the electronic resource.

At <NUM>, the data processing apparatus identifies, for each client device, user attributes of the user based on the digital component request.

In some implementations, the user attributes are identified using a predictive model based on the contextual data in the digital component request. For example, the predictive model can be configured to predict attributes of users that have accessed the electronic resource or the topics of the contents of the electronic resource.

In some implementations, the user is subscribed to the electronic resource with a user identifier, and the user attributes are identified using a user profile associated with the user identifier.

At <NUM>, the data processing apparatus sends, to the application of each client device, a digital component response. The digital component response includes (i) one or more digital components and (ii) attribute data specifying user attributes of the user. In response to receiving the attribute data, each client device is configured to update, based on the user attributes in the attribute data, accumulated user attribute data stored in a shared storage of the client device.

In some implementations, when the user attributes are identified using the predictive model based on the contextual data, the application can determine whether the accumulated user attribute data stored in the shared storage of the client device includes a keyed entry for the user attribute. If the accumulated user attribute data does not include the keyed entry, the application can generate a new keyed entry in the accumulated user attribute data, and assign an entry value for the new keyed entry based on the user attributes identified using the predictive model. If the accumulated user attribute data does include the keyed entry, the application can update the current entry value of the keyed entry in the accumulated user attribute data based on the user attributes identified using the predictive model. For example, to update the current entry value of the keyed entry, the application can increment or decrement the current entry value of the keyed entry.

In some implementations, when the user attributes are identified using the user profile associated with the user identifier, the application can determine whether the accumulated user attribute data stored in the shared storage of the client device includes a keyed entry for user attributes. If the aggregated user attribute data does not include the keyed entry, the application can generate a new keyed entry in the accumulated user attribute data, and assign an entry value for the new keyed entry based on the user attributes identified using the user profile. If the accumulated user attribute data does include the keyed entry, the application can update (e.g., replace) the entry value of the keyed entry in the accumulated user attribute data based on the user attributes identified using the user profile. In one example, a user interface of the electronic resource includes a script code to cause the application to update the accumulated user attribute data based on the user attributes in response to receiving the user attributes.

At <NUM>, the data processing apparatus obtains the accumulated user attribute data from the shared storage of each client device.

At <NUM>, the data processing apparatus generates an aggregated user attribute report for a set of aggregation keys using the obtained accumulated user attribute data. In particular, for each aggregation key, the data processing apparatus generates an aggregated data profile by aggregating the accumulated user attribute data from a subset of client devices that have accessed an electronic resource or a digital component identified by the aggregation key.

In some implementations, the aggregated profile for an aggregation key includes one or more metrics for the electronic resource or the digital component identified by the aggregation key. For example, the metrics can include a reach metric measuring the number of unique users in the subset of client devices that have accessed the electronic resource or the digital component identified by the aggregation key.

In some implementations, to improve data security and privacy, before and/or during generating the aggregated profile using the accumulated user attribute data from the subset of client devices, the data processing apparatus can apply privacy-preserving techniques to the accumulated user attribute data. These techniques can include anonymizing the data for each user, e.g., by removing any user identifiers from the data, applying k-anonymity techniques, and/or applying differential privacy techniques to the aggregated data. For example, to apply the differential privacy process, the data processing apparatus can add a random noise to the user attribute data of each of the subset of client devices before aggregating.

In some implementations, to improve data security and data privacy, the aggregated user attribute report can be generated by a secure aggregation system. The secure aggregation and reporting system can be a computing system separated from the digital component distribution system or a computing system that is a part of the digital component distribution system. If the secure aggregation and reporting system is a separate computing system from the digital component distribution system, the digital component distribution system can send an aggregation request to the secure aggregation and reporting system. The aggregation request includes the accumulated user attribute data received from each client device and the set of aggregation keys. The accumulated user attribute data received from a client device can be encrypted by the client device using an encryption key of the secure aggregation system. After the aggregated user attribute report has been generated by the secure aggregation and reporting system, the digital component distribution system can receive the aggregated data profiles from the secure aggregation system.

At <NUM>, the data processing apparatus adjusts, based on the estimated metrics, one or more distribution parameters for distributing digital components to client devices in response to digital component requests. For example, the data processing apparatus can adjust, based on the estimated metrics, keywords that must be matched, a list of geographic locations that the digital component is eligible to be provided, a list of user groups to which the digital component is eligible to be provided, parameters characterizing resources with which the digital component is eligible to be presented, and/or other appropriate distribution parameters.

At <NUM>, the data processing apparatus distributes the digital components to the client devices based on the distribution parameters.

<FIG> is a block diagram of an example computer system <NUM> that can be used to perform the operations described above. The system <NUM> includes a processor <NUM>, a memory <NUM>, a storage device <NUM>, and an input/output device <NUM>. Each of the components <NUM>, <NUM>, <NUM>, and <NUM> can be interconnected, for example, using a system bus <NUM>. The processor <NUM> is capable of processing instructions for execution within the system <NUM>. In some implementations, the processor <NUM> is a single-threaded processor. In another implementation, the processor <NUM> is a multi-threaded processor. The processor <NUM> is capable of processing instructions stored in the memory <NUM> or on the storage device <NUM>.

In various different implementations, the storage device <NUM> can include, for example, a hard disk device, an optical disk device, a storage device that is shared over a network by multiple computing devices (e.g., a cloud storage device), or some other large-capacity storage device.

In some implementations, the input/output device <NUM> can include one or more of a network interface devices, e.g., an Ethernet card, a serial communication device, e.g., and RS-<NUM> port, and/or a wireless interface device, e.g., an <NUM> card. In another implementation, the input/output device can include driver devices configured to receive input data and send output data to external devices <NUM>, e.g., keyboard, printer, and display devices.

Claim 1:
A computer-implemented method, comprising:
for each of a plurality of client devices,
receiving (<NUM>), by a digital component distribution system (<NUM>), from an application (<NUM>) running on the client device (<NUM>) of a user, a digital component request;
identifying (<NUM>), by the digital component distribution system, based on the digital component request, one or more user attributes of the user; and
sending (<NUM>), by the digital component distribution system, to the application, a digital component response comprising (i) one or more digital components and (ii) attribute data comprising the one or more user attributes of the user, wherein the application is configured to update, based on the one or more user attributes, accumulated user attribute data stored in a shared storage (<NUM>) of the client device in response to receiving the attribute data;
obtaining (<NUM>), by a secure aggregation system (<NUM>), from the shared storage of each of the plurality of client devices, the accumulated user attribute data stored in the shared storage of each client device;
generating (<NUM>), by the secure aggregation system, an aggregated user attribute report for one or more aggregation keys using the obtained accumulated user attribute data, comprising, for each of the one or more aggregation keys, obtaining an aggregated data profile that is generated by aggregating the accumulated user attribute data from a subset of the plurality of client devices that have accessed an electronic resource or a digital component identified by the aggregation key;
adjusting (<NUM>), by the digital component distribution system, based on the aggregated data profiles, one or more distribution parameters for distributing digital components to client devices in response to digital component requests; and
distributing (<NUM>), by the digital component distribution system, digital components to the client devices based on the distribution parameters.