Source: http://www.freshpatents.com/-dt20110630ptan20110161147.php
Timestamp: 2013-05-20 07:24:36
Document Index: 12302854

Matched Legal Cases: ['arty 116', 'arty 116', 'arty 116', 'arty 116', 'arty 116', 'arty 116', 'arty 116', 'arty 116', 'arty 116', 'arty 116', 'arty 116', 'arty 116']

Stimulus/response-based Binding Of Identifiers Across Information Domains While Maintaining Confidentiality n/a views for this patent on FreshPatents.comupdated 05/17/13
Patents sorted by company.	06/30/11 | Class 705 Monitor | RSS | Browse: Prev - Next Stimulus/response-based binding of identifiers across information domains while maintaining confidentiality Abstract: Disclosed are methods for extracting and using information about an entity that has a presence in a number of information domains. The entity has separate identifiers in each of several domains. Various techniques are described that bind together the identifiers of the entity across the domains. The results of the binding are provided to an interested party that can review information extracted about the entity's behavior in the multiple domains. The interested party is not given access to information that would compromise the confidentiality of the entity. A trusted broker has access to information about the behavior of the entity in the several domains. The broker analyzes that information and provides the analysis to the interested party, again without compromising the confidentiality of the entity. An “incentivizer” works with the broker to extract from the domains information that would be useful in binding together the different identifiers of the entity. ...
Agent: Motorola, Inc. - Schaumburg, IL, USInventors: Mark A. Gannon, Joshua B. Hurwitz, John Richard Kane, David W. Kravitz, Douglas A. KuhlmanUSPTO Applicaton #: #20110161147 - Class: 705 1413 (USPTO) - 06/30/11 - Class 705 Related Terms: Broker The Patent Description & Claims data below is from USPTO Patent Application 20110161147, Stimulus/response-based binding of identifiers across information domains while maintaining confidentiality.
The present application is related to four other applications, filed on an even date therewith and assigned to the same assignee. These four other applications are attorney docket numbers CML07506, CML07507, CML07529, and CML07530, and they are included herein by reference in their entireties.
The manufacturer of the soft drink is, of course, very interested in measuring the effectiveness of the advertising campaign he is running on the cable-television service. In this example, all of the information useful to the soft-drink manufacturer has been gathered by the separate domain owners: The ad-viewing behavior is recorded in association with the person\'s presence in the first domain (the cable-television service), while the soft-drink purchase behavior is recorded in association with the person\'s presence in the second domain (the grocery store). However, there is nothing to connect the viewing of the ad with the subsequent purchase of the soft drink.
This person probably has a separate “identifier” associated with his presence in each information domain, that is, he has a subscription account identifier with the cable-television provider, a loyalty card number at the grocery store, and one or more log-in account names for the social networks he visits. The problem of cross-domain information correlation can be restated as saying that it is very difficult to bind together these multiple identifiers to say that they all refer to the same person. If a cross-domain binding of the identifiers could be made, then behavior associated with the user\'s multiple identifiers could also be correlated. In this particular example, the ad viewing could be correlated with the soft-drink purchase. While that alone does not prove a cause and effect, the correlated information is of great interest to the soft-drink manufacturer. If such information were available for a large number of customers, then the manufacturer could draw reasonable conclusions about the effectiveness of his advertising campaign.
Useful as correlating these identifiers across information domains may be to the soft-drink manufacturer, customers may perceive here a violation of privacy. Such perceptions are likely to lower customer acceptance of cross-domain identifier binding. In a general sense, such correlations may begin to interfere with the customer\'s privacy. The example given above may be innocuous, and the customer might not fret if the soft-drink manufacturer concludes that a purchase was motivated by viewing an advertisement. However, other examples may be easily considered that would make the customer suspicious of an invasion of privacy. Indeed, people are already concerned if, after searching the web for information on leaf blowers, they start seeing ads for leaf blowers appear on the web pages they visit.
Preserving customer confidentiality across information domains is also important to the domain owners. Each domain owner is reluctant to share, without compensation, the potentially valuable information gathered about behavior within his domain. Also, the owner does not wish to jeopardize the gathering of future information or even lose the customer\'s business if the customer feels that his confidentiality is being compromised.
The above considerations, and others, are addressed by the present invention, which can be understood by referring to the specification, drawings, and claims. According to aspects of the present invention, in an attempt to bind together an entity\'s identifiers in two domains, a stimulus is created in association with a first identifier in a first domain. A response to the stimulus is noted in association with a second identifier in a second information domain. Because the response is known to be associated with the stimulus (the stimulus is created so that only the intended recipient can properly respond to it), the first and second identifiers are now known to refer to the same entity, and the two identifiers can be bound together. For example, a coupon (the stimulus) is sent to a cable-television subscriber (the first identifier), and the coupon is subsequently redeemed (the response) via a loyalty-card (the second identifier) program at a grocery store. The cable-television subscriber is then known to be the same entity as the holder of the loyalty card. A “cross-domain identifier” is produced that can be provided to an interested party (potentially for a fee or for other consideration). The cross-domain identifier allows the interested party to extract information about the entity\'s behavior in the domains. The interested party can use this information, for example, to assess the effectiveness of an advertising campaign or to extract other market intelligence.
FIG. 1 portrays a representative environment in which aspects of the present invention may be practiced. As a conceptual aid, the environment of FIG. 1 may be divided into three logical portions: First, the information domains 100 and 102 in which an entity exhibits some kind of observable behavior. Second, the three applications called the broker 112, the binder 114, and the incentivizer 118 extract useful information from the entity\'s observed behavior and package that useful information for another\'s use. The third logical portion is the interested party 116 that uses the packaged information.
Beginning the detailed description with the first logical portion mentioned above, it should first be noted that the entity itself is not shown in FIG. 1. For ease of the present discussion, the entity is usually taken to be a human being, but other entities are possible such as a business, social group, government entity, or other organization. It is the entity\'s behavior in the information domains 100, 102 that is most important for the present discussion.
The entity exhibits behavior in the information domains 100, 102, and that behavior is, at least to some extent, observed and recorded. For a cable-television domain 100, the entity\'s behavior includes what shows and advertisements he watches. Observable behavior in a retail domain 102 includes purchases made, products scanned even if not purchased, and interactions with “smart” signs and advertisements. Behavior in a public-safety domain includes arrests by the police, warnings given, and fines or other penalties assessed. The observable behavior of other domains 100, 102 can be easily imagined.
Observable behavior in the information domain 100 is associated with a “presence” 104 of the entity. This presence 104 is simply an identifier of the entity particular to this information domain 100. If the information domain 100 provides media, then the entity\'s presence 104 may be identified by the entity\'s subscription account number. In some media-providing domains (e.g., Internet-based providers), the presence identifier 104 may be a hardware or software token (e.g., a “cookie”). The presence 106 of the entity in a retail domain 102 can be a “loyalty card” number assigned to the entity. In a banking domain, the entity\'s presence can be identified by a checking account number. In an on-line social network, the entity can identify his presence by a log-in name or avatar. In general, the entity may have a different presence identifier 104, 106 in each of the information domains 100, 102 in which he exhibits behavior. The proliferation of these presence identifiers 104, 106 is one of the key elements driving some aspects of the present invention.
It may be useful to emphasize that the observed behavior of the entity within a particular information domain 100 is tied to the entity\'s identifier 104 in that domain 100, and only to that identifier 104. That is to say, the entity\'s behavior in the first information domain 100 is not, without further work, tied to the entity\'s identifier 106 in the second information domain 102.
The binder 114 discovers, by various techniques described below, that the presence identifiers 104 and 106 in the two information domains 100 and 102, respectively, are in fact associated with the same entity. That is to say, the binder 114 “binds together” the two (or more) presence identifiers 104, 106 of the entity. This binding can be very useful because it allows for the gathering of “cross-domain” intelligence. In general, at least one operator 108, 110 in each information domain 100, 102 observes and records the behavior of the entity within that one particular information domain. The work of the binder 114 allows a larger, cross-domain, picture of the entity\'s behavior to be developed.
A first technique usable by the binder 114 is illustrated in FIGS. 3a and 3b. The method begins at step 300 of FIG. 3a where the entity itself gives the binder 114 enough information to bind together the entity\'s presence identifiers 104, 106. In a straightforward example of this, the binder 114 (or the broker 112 acting on behalf of the binder 114) establishes a web site that invites the entity to log in and list his presence identifiers 104, 106. Also, when the entity uses one of the presence identifiers 104, 106, he can be invited to provide information about whatever other presence identifiers 104, 106 he may have. The entity can be given coupons or other monetary or non-monetary rewards to induce him to divulge this information. The entity is assured that this information will not be abused, and that the privacy of the entity will not be compromised.
In a somewhat less straightforward example, the binder 114 still gets the necessary binding information from the entity but gets the information indirectly. For example, the entity may perform a cross-domain transaction that contains enough information to perform the binding, and that cross-domain transaction is observed by the binder 114. An example of this involves an electronic coupon given to the entity in the first domain 100 and redeemed in another 102. (Permutations of this example are described below.) The coupon as issued is associated with a first presence identifier 104 of the entity in the first domain 100 (which in this example can be a media-providing domain). (The coupon “is associated with” the first presence identifier 104 by, for example, encrypting the presence identifier 104 within the electronic coupon.) When the coupon is redeemed in a retail domain 102, the entity uses the loyalty card issued to him by the retailer. This loyalty card serves as the entity\'s presence identifier 106 in the retail domain 102. When the binder 114 is informed about the coupon clearance (this informing is described in detail below), the binder 114 reasonably concludes that the two presence identifiers 104, 106 associated with the coupon belong to the same entity, and the binder 114 performs the binding.
Regardless of how the binder 114 receives the necessary information, the binder 114 performs the binding and then produces, in step 302 of FIG. 3a, a “cross-domain identifier.” As the output of the binding process, the cross-domain identifier is an important concept. In short, it provides access to the binding and, in consequence, access to some behavioral observations concerning the entity in at least some of the domains 100, 102 involved in the binding. However, because the privacy of the entity is a major concern, the cross-domain identifier is so constructed that it does not allow access to all information about the entity.
FIG. 4 presents an idealized structure for the cross-domain identifier 400. FIG. 4 shows that by accessing the cross-domain identifier 400, a party is given access to some behavioral information 402, 404 associated with the entity. Consider the case where the first information domain 100 is a media-providing domain, and the second information domain 102 is a retail domain. Then, after the cross-domain identifier 400 is constructed binding together the entity\'s presence identifiers 104, 106 in these two domains 100, 102, the cross-domain identifier 400 may provide access to observations 402 of media-consumption activities (e.g., what shows and advertisements the entity watched) from the first domain 100 and access to observations 404 of retail activities (e.g., a list of products purchased by the entity, products scanned but not purchased, and interactions with intelligent signs and advertisements) from the second domain 102.
Note, however, that for privacy reasons, the cross-domain identifier 400 generally does not provide access to the entity\'s presence identifiers 104, 106 themselves because that could lead to a loss of privacy. Also, even if the binder 114 has gathered information that could reveal the identity of the entity, that information is generally not made accessible through the cross-domain identifier 400. This potentially identity-revealing information can include, in addition to the presence identifiers 104, 106, information about the entity\'s name, address, telephone number, credit-card and bank-account numbers, social-security numbers, automobile license plate number, other identifiers, biometrics such as voice samples, photographs, and software or hardware identifiers (including tokens or “cookies”).
Even withholding access to the entity\'s presence identifiers 104, 106 and information about the entity\'s identity may not provide enough security in some situations, however. Therefore, in these situations, the cross-domain identifier 400 is constructed to only give access to general information about behavior rather than giving access to specific instances of observed behavior. As one example, in step 304, the cross-domain identifier 400 is constructed to provide access to information about a number of entities. That information may be accessible on an entity-by-entity basis or may only be available as statistical results covering a population of entities. An entity\'s confidential information is more carefully guarded when the cross-domain identifier 400 only provides access to the results of high-level analysis. That type of information is very valuable to many potential interested parties 116, and indeed several interested parties 116 may only want the high-level analysis. In some embodiments, the price that the interested party 116 pays for access to a cross-domain identifier 400 is determined, in part, by the level of behavioral detail that the interested party 116 can access through the cross-domain identifier 400. As discussed below, the cross-domain identifier 400 can be more valuable if it points to information extracted by an analysis of a large population.
FIGS. 5a and 5b present a different method usable by the binder 114. The difference between this method and the method of FIGS. 3a and 3b lies in how the binder 114 receives enough information to perform the binding of the entity\'s presence identifiers 104 and 106. The method of FIGS. 5a and 5b begins at step 500 when a stimulus is created in association with a first presence identifier 104 of the entity in the first domain 100. The stimulus here is intended to induce the entity to perform a specific cross-domain operation. Turning to our familiar example, the stimulus can be a coupon, electronically formed to include an association with the entity\'s presence identifier 104. Such entity-specific coupons are already known (even though the use of them as in the method of FIGS. 5a and 5b is new) and are sent, for example, in e-mail advertisements or are downloadable from a web site once the entity has asserted one of his identifiers by logging in. Other stimuli are possible including contest entries.
A more complicated scenario is also possible. The original recipient of the coupon may be allowed to pass the coupon on to a friend who is then allowed to redeem the coupon for himself. The coupon can be constructed so that an electronic “chain of custody” is created. This chain-of-custody information is given to the binder 114 in step 502. From the chain, the binder 114 can bind together the friend\'s presence identifier in the coupon-providing domain with the friend\'s presence identifier in the retail domain when the friend redeems the coupon. In this scenario, of course, there is not enough information to bind the presence identifiers of the original coupon recipient.
Once the binder 114 binds the presence identifiers of the coupon\'s redeemer (whether or not that is the same entity that originally received the coupon), the method of FIGS. 5a and 5b proceeds in parallel with the method of FIGS. 3a and 3b. A cross-domain identifier 400 is created in step 506. The cross-domain identifier 400 may provide information about a population of customers (step 508 of FIG. 5b) and may provide access to ongoing behavioral information (step 510). The cross-domain identifier 400 is provided to an interested party in step 512.
Before leaving the method of FIGS. 5a and 5b, one point should be noted. If the coupon is redeemed but not by the original coupon recipient, then the chain-of-custody is itself potentially valuable information. It may be reasonably inferred that the original recipient is a friend or acquaintance of the second person in the chain, the second person is a friend or acquaintance of the third person in the chain (if any), and so on. Thus, by observing the passing on of the coupon, the method of FIGS. 5a and 5b can generate useful information about social contacts. While not specifically relevant to the task of binding together presence identifiers, this information can be passed along to the broker 112 that may be able to use it.
Yet another binding method is presented in FIGS. 6a and 6b. In step 600, the behavior observed in a first domain 100 is analyzed. Each usable piece of information is associated with one or more presence identifiers 104. Then in step 602, the behavior observed in a second domain 102 is analyzed. Again, the usable observations are associated with one or more presence identifiers 106. In step 604, the binder 114 attempts to extract from these observations likely bindings of presence identifiers 104, 106 in the two domains.
It should be noted that in steps 600 and 602, the binder 114 may need to process behavioral observations associated with innumerable presence identifiers 104, 106 and thus with innumerable entities before beginning to construct even hypothetical bindings. This method, in contradistinction to the binding methods of FIGS. 3a, 3b, 5a, and 5b mostly rewards only those binders 114 that have access to information on large populations of entities. Also, the more information domains available to the broker 114 for analysis, the better, as the broker 114 may be better able to extract patterns of behavior when more examples in more domains are available for contemplation.
Note that in step 608 of FIG. 6b, the cross-domain identifier 400 may include population statistics about multiple entities, just as in the previous methods. Be aware that this is another statistical step in addition to the statistics that the method of FIGS. 6a and 6b often applies when proposing a single binding (in step 604 of FIG. 6a). If the binder 114 is fortunate enough to have access to information on large populations of entities, then the value of this statistical population information may completely outweigh any concern about the uncertainty associated with any particular binding.
Before leaving the discussion of binding methods to talk about the broker 112, it should be noted that the three binding methods given above need not be implemented in separate embodiments. A single binder 114 can use whatever method, or whatever combination of methods, is most appropriate given the information resources it is allowed to analyze. Also, the steps in each flowchart need not occur exactly in the order given. For example, the binder 114 may be always “pre-analyzing” behavioral information and then only create actual bindings when called upon to do so. Again, especially in the case of the method of FIGS. 6a and 6b, the binder 114 may need to revisit a cross-domain identifier 400 that it earlier produced when the binder 114 comes upon more information that either throws the previous binding into doubt or increases the level of confidence in that binding.
Now turning to the broker 112, FIGS. 7a and 7b present a first exemplary method. Ignore the first two steps 700, 702 of FIG. 7a for the moment. In step 704, the broker 112 receives behavioral observations from an operator 108 in the first information domain 100. As mentioned above in reference to step 600 of FIG. 6a, the usable observations are usually associated with one or more presence identifiers 104. However, the broker 112 can also make use of observations that are not tied to a specific presence identifier 104. In step 706, the broker 112 receives behavioral observations from an operator 110 in the second information domain 102. These steps 704, 706 are repeated for as many information domains as the broker 112 is allowed to monitor. In the method of FIGS. 7a and 7b, these steps 704, 706 continue on as long as the broker 112 is operating. (Note that in some embodiments, the broker 112 receives the information of steps 704 and 706 in association with the cross-domain identifier 400 received in step 712, described below. In those embodiments, steps 704 and 706 are sub-steps of step 712.)
In step 714, the broker 112 provides results of its analyses to an interested party 116. For security\'s sake, these results can be provided via a cross-domain identifier 400 created by the binder 114. The broker 112 may sell this information or exchange it for something else of value.
Return now to step 700 of FIG. 7a. In some embodiments, the broker 112 works closely with one or more incentivizers 118 (described in more detail below). Sometimes, the incentivizer 118 works through the broker 112 to access an information domain 100. In step 700, the broker 112 receives instructions from the incentivizer 118 detailing what the incentivizer 118 wants the broker 112 to do. For a first example, the incentivizer 118 can tell the broker 112 what type of analysis it wants to see. Note that in some cases, the incentivizer 118 is working directly for an interested party 116. If so, then the incentivizer 118 cannot have the same level of access to confidential information in the domain 100 that the trusted broker 112 enjoys. Thus, requests for specific kinds of analysis (including specifics about data gathering) are often made through the trusted broker 112.
In a second example, the rule from the incentivizer 118 specifies particular actions that the incentivizer 118 wishes to have happen in the domain 100. Recall the stimulus/response method of binding described above in reference to FIGS. 5a and 5b. The incentivizer 118 can tell the broker 112 in step 700 of FIG. 7a what kinds of stimuli the incentivizer 118 wishes to send into the domain 100. The incentivizer 118 can also specify the types of entities that should receive the stimulus, and the trusted broker 112 may be the only entity outside the domain 100 that knows enough about the entities to fulfill this request.
In general, the behavior analyzed in steps 704 and 706 can be any behavior observed by the operators 108, 110 in the various domains 100, 102 including media-consumption behavior, retail behavior, behavior with respect to a social or other association, and the like. FIGS. 8a and 8b provide a rather specific example of behavior that the broker 112 may analyze. The method begins as in the method of FIGS. 7a and 7b. In step 710 of FIG. 8a, the broker 112 analyzes the received behavioral observations.
The interested parties 116 decide how they want to approach the social connector. For example, an interested party may choose to send a coupon for a relevant product or service to the social connector. For security\'s sake, the interested party 116 may not be given enough information in step 802 to do this directly, so the interested party 116 sends a coupon-generating rule to the broker 112 in step 804. Although the interested party 116 is in general not an incentivizer 118, the broker 112 receives and processes the rule in the same manner as discussed above in reference to step 700 of FIG. 7a (where the broker 112 receives a rule from an incentivizer 118). In step 806 of FIG. 8a, the broker 112 takes action based on the rule, for example by generating and sending a coupon or by instructing an operator 108 in the first domain 100 to do so.
In step 808 of FIG. 8b, the broker 112 receives information about the redemption of the coupon. Of course, if this coupon is redeemed in association with a second presence identifier 106 of the entity in a second information domain 102, then the broker 112 can send this information to the binder 114 to bind together the entity\'s two presence identifiers 104, 106. In other situations, the binding was done before the interested party 116 got involved. Even if the binding was not done and cannot be done (e.g., the coupon was redeemed, but the entity did not use a retail loyalty card), the broker 112 has still provided a valuable service to the interested party 116 and, through that party 116, to the social connector himself.
FIGS. 9a and 9b present an exemplary method usable by the incentivizer 118. In step 900, the incentivizer 118 sends to the broker 112 a rule for carrying out an operation in the first domain 100. (This is the same rule that the broker 112 receives in step 700 of FIG. 7a, discussed above.) In the particular embodiment of FIGS. 9a and 9b, this rule specifies how a particular transaction is to begin, that is to say, how to contact an entity via the entity\'s presence identifier 104 in the first domain 100 and how to persuade the entity to perform in a specific manner. (In other embodiments, the incentivizer 118 can operate without contacting the entity.) In this embodiment, the incentivizer 118 operates through the broker 112 because, as noted above in the discussion of the broker 112, the broker 112 often has access to an operator 108 in the domain 100 that the incentivizer 118 does not have.
Turning back to our common example of the coupon, the incentivizer 118 may direct, in step 900, the broker 112 to generate and send a coupon associated with the entity\'s presence identifier 104 in a media-providing domain 100. The coupon is redeemed in association with the entity\'s presence identifier 106 in the retail domain 102. Thus, the incentivizer 118 has incented the entity to perform a cross-domain transaction that results in gathering the information needed by the broker 114 to bind together these two identifiers 104, 106 of the entity. In this situation, the broker 112 may have monitored the transaction and sent the information to the binder 114. The results may then be received by the incentivizer 118 via a cross-domain identifier 400 created by the binder 114.
In step 904, the incentivizer 118 rewards at least one operator 108, 110 in at least one of the domains 100, 102. (The reward may pass through the broker 112 as appropriate.) The reward is another incentive, in this case an incentive to the operator 108, 110 to cooperate with the broker 112 in providing the incentive that produced the desired behavior in the entity. Different rewards are appropriate to different operators 108, 110 in different domains 100, 102. Rewards can include, for example, money, publicity, increased traffic directed toward the operator\'s domain, access to information (such as that gathered by the broker 112), increased public safety (when, for example, a domain is a public-safety jurisdiction), increased number of customers, and certification of compliance with a regulation.
In some embodiments, the incentivizer 118 is not yet done with the entity but may, based on the entity\'s response to the incentive, send a revised rule to the broker 112 in step 906. For example, an entity that often redeems coupons for products promoted by the incentivizer 118 can be rewarded by higher-value coupons or other considerations. Indeed, the incentivizer 118 can even reward the entity directly in step 908 of FIG. 9b by sending a reward associated with the entity\'s presence identifier 104, 106 in one of the information domains 100, 102. Note that even in this case, the reward may need to pass through the broker 112 because the incentivizer 118 may not have enough information to send the reward directly. In other embodiments, the incentivizer 118 need not send a revised rule because the original rule sent to the broker 112 can be adaptive to cover these cases.
A distinction between the incentivizer 118 and the broker 112 should be drawn. In some cases, the incentivizer 118 is a neutral party, working mainly to help the binder 114 get enough information to do its work. In other cases, however, the incentivizer 118 works for a commercial interest, such as the interested party 116, and pushes coupons and advertisements for that party\'s commercial interest. These non-neutral incentivizers 118 are able to work without compromising the entity\'s confidential information because these incentivizers 118 are made to work through the neutral, and trusted, broker 112.
The methods of FIGS. 9a, 9b, and 10 are simply examples showing how the incentivizer 118 can induce entities to act in particular ways that will in turn help the entities themselves or help other participants (such as the operators 108, 110, the broker 112, and the binder 114) to perform their tasks more effectively.
FIG. 11 shows how a coupon can be generated specifically for use by an entity while preserving the confidentiality of that entity\'s private information. FIG. 11 begins with message flow 1100 when an incentivizer 118 registers with the broker 112 for services. The incentivizer 118 sends rules to the broker 112 detailing a coupon-generation function that the broker 112 will implement.
1104 is an optional message flow. Here, the entity registers its presence identifier 106 (e.g., a loyalty card for use in the retail domain) with the operator 110 of the retail domain. By registering, the entity indicates his willingness to participate in the services offered by the incentivizer 118. (In some embodiments, the entity\'s willingness to participate can be indicated by his redemption of a coupon in message flow 1116.) In some embodiments, this information is then sent by the operator 110 to the broker 112.
In message flow 1108, the entity registers with the coupon-derivation function and receives a pseudonym that uniquely identifies it. The entity also registers the loyalty card it uses in the retail domain. Note that the message flow 1108 may not, in some embodiments, carry the loyalty-card information. (That information may go only to the coupon-derivation function which might run on a device owned by the entity rather than a device run by the operator 108.) Note that in the example of FIG. 11, the broker 112 does not know the entity\'s pseudonym, because that pseudonym is created by the entity and the coupon-derivation function (distributed by the operator 108) working together. Note that in some embodiments, the message flow 1108 goes directly to the binder 114 without the broker 112 seeing this information.
As this is going on, message flow 1112 proceeds. Here, the operator 110 collects observations of the entity\'s behavior in the retail domain. These observations are associated with the entity\'s retail loyalty card. Of particular interest are observations of purchases, by the entity, of the products promoted by the incentivizer 118. (In a slightly more complicated scenario, observations of purchases of products directly competing with the products promoted by the incentivizer 118 are also of great interest.) In the particular embodiment of FIG. 11, message flow 1112 continues from the operator 110 in the retail domain to the coupon-derivation function associated with the entity in the media-providing domain. Here, the coupon-derivation function uses the loyalty-card information registered by the entity in message flow 1108 to obtain the observations of the entity\'s retail behavior (at least those observations relevant to the products promoted by the incentivizer 118).
Now knowing something about the entity\'s retail habits, the coupon-derivation function, in message flow 1114, creates and sends a coupon to the entity, probably in association with an advertisement presented to the entity in the media-providing domain. The coupon is made specifically to appeal to the entity\'s interests as revealed by the behavioral observations made in the retail domain. As one example, the entity may be seen to be a loyal consumer of the products promoted by the incentivizer 118, and the coupon can reward that loyalty. As another example, the entity may be seen to prefer products that directly compete with the products promoted by the incentivizer 118, and the coupon is made to entice the entity away from the competitor. The coupon is electronically generated and includes, probably encrypted with a public encryption key of the broker 112, the pseudonym of the entity (generated in message flow 1108). This information is used to track the coupon (and possibly to limit its use to this particular entity and to allow its redemption only in association with the entity\'s retail loyalty card).
In message flow 1122, the incentivizer 118 rewards at least one operator 108, 110. (As mentioned above, the incentivizer 118 may reward all of the operators 108, 110 that participated in the transaction.) The reward can be monetary or can include better intelligence as to how entities are behaving in the operator\'s domain.
The scenario of FIG. 12 diverges from that of FIG. 11 in message flow 1210. Here, the coupon-derivation function registers the entity\'s pseudonym and a routable identifier with the broker 112.
Message flow 1212 of FIG. 12 is similar to message flow 1110 of FIG. 11: The operator 108 observes the entity\'s behavior in the media-providing domain. Meanwhile, in the right portion of message flow 1214, the operator 110 observes the entity\'s behavior in the retail domain. (The left portion of message flow 1214, from the operator 110 to the operator 108, is considered below.)
In message flow 1216, a coupon is created in association with the entity\'s presence identifier 104 in the media-providing domain. The first time this happens for a given entity the coupon does not include the entity\'s loyalty card number because the coupon-derivation function does not know it. The coupon does, however, include the pseudonym assigned to the entity in message flow 1208.
This binding information is used to streamline all future interactions between the entity and the coupon-derivation function. Returning to the left portion of message flow 1214, the coupon-derivation function can now use the loyalty card information to receive observations of the entity\'s retail behavior from the retail operator 110.
Note that as a result of running through the scenario of FIG. 12, the binder 114 has been able to bind identifiers of the entity across the domains. Note also that the confidentiality of the entity is strongly preserved, as the broker 112 only knows the entity in the media-providing domain in terms of the routable identifier and pseudonym and not in terms of the entity\'s actual identifier 104.
In message flow 1306, observations of the entity\'s behavior in the media-providing domain are collected by the operator 108 and sent along to the broker 112. The incentivizer 118 sends its coupon rules to the broker 112 in message flow 1308.
The behavior of the entity in the first domain is observed by an operator 108 in that domain, and the observations are sent to the broker 112 in message flow 1404. In this scenario, the first domain can be a communications domain, and the behavioral observations can include call logs and the like. From this (and possibly other) information, the broker 112 determines that the entity is a social connector and that the entity is planning an event (or, at least, that a social event will occur soon, such as a birthday of a member of the entity\'s social group).
The entity redeems the coupons (or otherwise responds appropriately to the retailers\' incentives) in the retail domain in message flow 1412. Message flow 1414 carries the coupon-redemption information to the broker 112. If it has not done so already, the binder 114 uses this redemption information, along with the information already at hand in the broker 112, to bind together the presence identifiers 104, 106 of the entity across the domains.
Aspects of the present invention, as described above, can be readily adapted to other scenarios. For a first example, an electronic shopping list can be presented to various incentivizers 118 (representing manufacturers) and operators 110 (representing retailers) in an auction. The results of the auction can be used to procure the items on the list as well as to provide information useful for optimizing the supply-chains of the participating manufacturers and retailers. In a second example, an entity\'s browsing for a product (that is, electronic “window shopping”) can be observed and reported to a relevant incentivizer 118. The incentivizer 118 can then send a targeted advertisement for the product to the entity. These two examples are combined when the product-browsing behavior of numerous entities is observed, and, based on those observations, a statistical analysis is produced. The analysis can be sold as market information to manufacturers and retailers.
In another scenario, an entity wishes to provide information but wishes to withhold any information that could identify him. For example, the person may be a source for an interesting news story, or may have inside information on a nefarious activity. However, the recipient of the information does not want to act on the tip unless there is some way to authenticate either the tip itself or its source. The source can send his tip to a trusted broker 112, and the broker 112 can correlate this tip with previous tips sent by the same source. (The broker 112 need not know the actual identity of the source but can establish some reliable log-in so that the broker 112 recognizes this source and can correlate the present tip with the source\'s previous tips.) Then the broker 112 provides the tip to the relevant recipient (newspaper, police) with an estimate of the trustworthiness of the source, all the while maintaining the secrecy of the source\'s identity. The broker 112 may also package related tips from more than one source and present the package to the recipient, thus shielding the identities of the sources even more. This is an example of the broker 112 making use of the enormous amount of information it receives to provide a valuable service.
In a scenario similar to that of the tipster described just above, the broker 112 can provide past employment information to a potential employer. As a trusted intermediary, the broker 112 can provide honest assessment of the entity\'s past employment while anonymizing the information. In one case, the potential employer tells the broker 112 the employer\'s specific hiring needs, and the broker 112 reviews its information to present suitable candidates that do not have bad assessments. The incentive for a previous employer to provide this information to the broker 112 is similar to the case of the businesses sharing individual business records as given above: By sending in information, the participants make the employment database of the broker 112 more complete and accurate which can help the participant in the future when that participant needs to hire someone.
In some situations, the incentivizer 118 may need to incent the entity itself rather than incent an operator 108 in an information domain 100. For example, for a web-based domain 100, behavior observations (e.g., web sites visited) can be made on a PC operated by the entity. Then, the techniques described above can be used, with the incentivizer 118 sending a reward to the entity for allowing observational software to be downloaded to the entity\'s PC. This observational software can add to the observations made by the cookies typically downloaded by individual web sites.
Download full PDF for full patent description/claims.You can also Monitor Keywords and Search for tracking patents relating to this Stimulus/response-based binding of identifiers across information domains while maintaining confidentiality patent application.Patent Applications in related categories: 20130117083 - System and process for distributing coupon codes or discount offers via short code and sms mobile and internet technolog for a convenience fee - Among other things, there are disclosed systems and methods for providing coupons on demand to a consumer, to make the process of offering coupons and redeeming coupons more efficient. Embodiments of such systems may include a server reachable by mobile telephones or other communication devices with a database of coupon ...
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