Patent Publication Number: US-2020301974-A1

Title: Search suggestions within a client instance

Description:
BACKGROUND 
     The present disclosure relates generally to providing search suggestions within a network environment cloud infrastructure client instance (also referred to herein as a client instance or instance). 
     This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present disclosure, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements are to be read in this light, and not as admissions of prior art. 
     Organizations, regardless of size, rely upon access to information technology (IT) and data and services for their continued operation and success. A respective organization&#39;s IT infrastructure may have associated hardware resources (e.g. computing devices, load balancers, firewalls, switches, etc.) and software resources (e.g. productivity software, database applications, custom applications, and so forth). Over time, more and more organizations have turned to cloud computing approaches to supplement or enhance their IT infrastructure solutions. 
     Cloud computing relates to the sharing of computing resources that are generally accessed via the Internet. In particular, a cloud computing infrastructure allows users, such as individuals and/or enterprises, to access a shared pool of computing resources, such as servers, storage devices, networks, applications, and/or other computing based services. By doing so, users are able to access computing resources on demand that are located at remote locations, which resources may be used to perform a variety of computing functions (e.g., storing and/or processing large quantities of computing data). For enterprise and other organization users, cloud computing provides flexibility in accessing cloud computing resources without accruing large up-front costs, such as purchasing expensive network equipment or investing large amounts of time in establishing a private network infrastructure. Instead, by utilizing cloud computing resources, users are able redirect their resources to focus on their enterprise&#39;s core functions. 
     A cloud-based information technology platform may include a virtual server that enables aspects of a client instance. One or more software applications running in the client instance may enable a user to search for information by, for example, entering a search query into a search field provided in the application and returning search results based on the search query. However, it may be tedious or inefficient, particularly in cases where the user is accessing the client instance via a mobile device, for the user to enter a full or complete search query. 
     SUMMARY 
     A summary of certain embodiments disclosed herein is set forth below. It should be understood that these aspects are presented merely to provide the reader with a brief summary of these certain embodiments and that these aspects are not intended to limit the scope of this disclosure. Indeed, this disclosure may encompass a variety of aspects that may not be set forth below. 
     As presently disclosed, a cloud-based information technology platform may include a virtual server that enables a network environment cloud infrastructure client instance (also referred to herein as a client instance or instance). A software application (e.g., a browser application, a productivity suite application, a map application, a mobile application, and so forth) running in the client instance may enable a user to search for information by, for example, entering a search query into a search field and returning search results based on the search query. To create a more user-friendly experience, particularly in the case where the user is accessing the client instance via a mobile device, the application may suggest search queries (also referred to herein as search suggestions) as the user is entering the search query. That is, the application may suggest the search suggestions based on a partial search query. 
     The search suggestions may include user search suggestions that are based on previous search queries performed by the user and instance search suggestions that are based on previous search queries performed on the instance. In some embodiments, the application may filter the instance search suggestions based on filter criteria associated with the user or a device being employed by the user, such as an interface (e.g., mobile or web portal) used by the user, a search context (e.g., associated with a software application or page at which the search query is entered), user group that the user belongs to, domain used by the user, and so on. The application may remove or downweight search suggestions that include blacklisted terms. The application running on the client instance may rank the search suggestions (e.g., based on frequency and/or recency) and enable the user to select those ranked search suggestions that meet or exceed a threshold. In this manner, the application may provide relevant search suggestions to the user without the user having to enter a full search query, saving time and providing a better user experience. 
     Various refinements of the features noted above may exist in relation to various aspects of the present disclosure. Further features may also be incorporated in these various aspects as well. These refinements and additional features may exist individually or in any combination. For instance, various features discussed below in relation to one or more of the illustrated embodiments may be incorporated into any of the above-described aspects of the present disclosure alone or in any combination. The brief summary presented above is intended only to familiarize the reader with certain aspects and contexts of embodiments of the present disclosure without limitation to the claimed subject matter. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Various aspects of this disclosure may be better understood upon reading the following detailed description and upon reference to the drawings in which: 
         FIG. 1  is a block diagram of an embodiment of a cloud architecture in which embodiments of the present disclosure may operate; 
         FIG. 2  is a schematic diagram of an embodiment of a multi-instance cloud architecture in which embodiments of the present disclosure may operate; 
         FIG. 3  is a block diagram of a computing device utilized in a computing system that may be present in  FIG. 1 or 2 , in accordance with aspects of the present disclosure; 
         FIG. 4  is a flowchart of a process for providing search suggestions within a client instance of  FIG. 2 , according to embodiments of the present disclosure 
         FIG. 5  is a view of a web portal providing search suggestions within the client instance of  FIG. 2 , according to embodiments of the present disclosure; 
         FIG. 6  is a view of a web portal listing previously performed search queries on the client instance of  FIG. 2  in a table, according to embodiments of the present disclosure; 
         FIG. 7  is a view of a web portal listing search suggestions in a table that were generated based on search queries previously performed on the client instance of  FIG. 2 , according to embodiments of the present disclosure; 
         FIG. 8  is a view of a web portal listing blacklisted terms in a table, according to embodiments of the present disclosure; 
         FIG. 9  is a view of a mobile interface providing search suggestions within a client instance of  FIG. 2 , according to embodiments of the present disclosure; and 
         FIG. 10  is a view of a web portal providing search suggestions within a client instance of  FIG. 2  for a user that does not have a role as system administrator, according to embodiments of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
     One or more specific embodiments will be described below. In an effort to provide a concise description of these embodiments, not all features of an actual implementation are described in the specification. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers&#39; specific goals, such as compliance with system-related and enterprise-related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure. 
     As used herein, the term “computing system” refers to an electronic computing device such as, but not limited to, a single computer, virtual machine, virtual container, host, server, laptop, and/or mobile device, or to a plurality of electronic computing devices working together to perform the function described as being performed on or by the computing system. As used herein, the term “medium” refers to one or more non-transitory, computer-readable physical media that together store the contents described as being stored thereon. Embodiments may include non-volatile secondary storage, read-only memory (ROM), and/or random-access memory (RAM). As used herein, the term “application” refers to one or more computing modules, programs, processes, workloads, threads and/or a set of computing instructions executed by a computing system. Example embodiments of an application include software modules, software objects, software instances and/or other types of executable code. 
     As presently disclosed, a cloud-based information technology platform may include a virtual server that enables a network environment and supports aspects of a service provider cloud infrastructure client instance (also referred to herein as a client instance or instance). A software application running in the client instance may enable a user to search for information by, for example, entering a search query into a search field and returning search results based on the search query. To create a more user-friendly experience, particularly in the case where the user is accessing the client instance via a mobile device, the application may suggest search queries (also referred to herein as search suggestions) as the user is entering the search query. That is, the application may suggest the search suggestions based on a partial search query. 
     The search suggestions may include user-based search suggestions that are based on previous search queries performed by the user and instance-based search suggestions that are based on previous search queries performed on the instance (e.g., within a organization or organizational unit associated with that instance). In some embodiments, the application may filter the search suggestions based on filter criteria associated with the user, such as an interface (e.g., mobile or web portal) used by the user, a search context (e.g., associated with a software application or page at which the search query is entered), a user group that the user belongs to, a domain used by the user, and so on. The application may remove or downweight (e.g., lower the rank of) the search suggestions that include blacklisted terms. The application may rank the search suggestions (e.g., based on frequency and/or recency) and enable the user to select those ranked search suggestions that meet or exceed a threshold. In this manner, the application may provide relevant search suggestions to the user without the user having to enter a full search query, saving time and providing a better user experience. 
     With the preceding in mind, the following figures relate to various types of generalized system architectures or configurations that may be employed to provide services to an organization in a multi-instance framework and on which the present approaches may be employed. Correspondingly, these system and platform examples may also relate to systems and platforms on which the techniques discussed herein may be implemented or otherwise utilized. Turning now to  FIG. 1 , a schematic diagram of an embodiment of a cloud computing system  10  where embodiments of the present disclosure may operate, is illustrated. The cloud computing system  10  may include a client network  12 , a network  14  (e.g., the Internet), and a cloud-based platform  16 . In some implementations, the cloud-based platform  16  may be a configuration management database (CMDB) platform. In one embodiment, the client network  12  may be a local private network, such as local area network (LAN) having a variety of network devices that include, but are not limited to, switches, servers, and routers. In another embodiment, the client network  12  represents an enterprise network that could include one or more LANs, virtual networks, data centers  18 , and/or other remote networks. As shown in  FIG. 1 , the client network  12  is able to connect to one or more client devices  20 , such as a desktop computer  20 A, a laptop computer  20 B, and a mobile device  20 C (e.g., a smartphone), so that the client devices  20  are able to communicate with each other and/or with the network hosting the platform  16 . The client devices  20  may be computing systems and/or other types of computing devices generally referred to as Internet of Things (IoT) devices that access cloud computing services, for example, via a web browser application or portal  21 , a mobile interface  22 , or via an edge device  23  that may act as a gateway between the client devices  20  and the platform  16 .  FIG. 1  also illustrates that the client network  12  includes an administration or managerial device, agent, or server, such as a management, instrumentation, and discovery (MID) server  24  that facilitates communication of data between the network hosting the platform  16 , other external applications, data sources, and services, and the client network  12 . Although not specifically illustrated in  FIG. 1 , the client network  12  may also include a connecting network device (e.g., a gateway or router) or a combination of devices that implement a customer firewall or intrusion protection system. 
     For the illustrated embodiment,  FIG. 1  illustrates that client network  12  is coupled to a network  14 . The network  14  may include one or more computing networks, such as other LANs, wide area networks (WAN), the Internet, and/or other remote networks, to transfer data between the client devices  20  and the network hosting the platform  16 . Each of the computing networks within network  14  may contain wired and/or wireless programmable devices that operate in the electrical and/or optical domain. For example, network  14  may include wireless networks, such as cellular networks (e.g., Global System for Mobile Communications (GSM) based cellular network), IEEE 802.11 networks, and/or other suitable radio-based networks. The network  14  may also employ any number of network communication protocols, such as Transmission Control Protocol (TCP) and Internet Protocol (IP). Although not explicitly shown in  FIG. 1 , network  14  may include a variety of network devices, such as servers, routers, network switches, and/or other network hardware devices configured to transport data over the network  14 . 
     In  FIG. 1 , the network hosting the platform  16  may be a remote network (e.g., a cloud network) that is able to communicate with the client devices  20  via the client network  12  and network  14 . The network hosting the platform  16  provides additional computing resources to the client devices  20  and/or the client network  12 . For example, by utilizing the network hosting the platform  16 , users of the client devices  20  are able to build and execute applications for various enterprise, IT, and/or other organization-related functions. In one embodiment, the network hosting the platform  16  is implemented on the one or more data centers  18 , where each data center could correspond to a different geographic location. Each of the data centers  18  includes a plurality of virtual servers  26  (also referred to herein as application nodes, application servers, virtual server instances, application instances, or application server instances), where each virtual server  26  can be implemented on a physical computing system, such as a single electronic computing device (e.g., a single physical hardware server) or across multiple-computing devices (e.g., multiple physical hardware servers). Examples of virtual servers  26  include, but are not limited to a web server (e.g., a unitary Apache installation), an application server (e.g., unitary JAVA Virtual Machine), and/or a database server (e.g., a unitary relational database management system (RDBMS) catalog). 
     To utilize computing resources within the platform  16 , network operators may choose to configure the data centers  18  using a variety of computing infrastructures. In one embodiment, one or more of the data centers  18  are configured using a multi-tenant cloud architecture, such that one of the server instances  26  handles requests from and serves multiple customers. Data centers  18  with multi-tenant cloud architecture commingle and store data from multiple customers, where multiple customer instances are assigned to one of the virtual servers  26 . In a multi-tenant cloud architecture, the particular virtual server  26  distinguishes between and segregates data and other information of the various customers. For example, a multi-tenant cloud architecture could assign a particular identifier for each customer in order to identify and segregate the data from each customer. Generally, implementing a multi-tenant cloud architecture may suffer from various drawbacks, such as a failure of a particular one of the server instances  26  causing outages for all customers allocated to the particular server instance. 
     In another embodiment, one or more of the data centers  18  are configured using a multi-instance cloud architecture to provide every customer its own unique customer instance or instances. For example, a multi-instance cloud architecture could provide each customer instance with its own dedicated application server and dedicated database server. In other examples, the multi-instance cloud architecture could deploy a single physical or virtual server  26  and/or other combinations of physical and/or virtual servers  26 , such as one or more dedicated web servers, one or more dedicated application servers, and one or more database servers, for each customer instance. In a multi-instance cloud architecture, multiple customer instances could be installed on one or more respective hardware servers, where each customer instance is allocated certain portions of the physical server resources, such as computing memory, storage, and processing power. By doing so, each customer instance has its own unique software stack that provides the benefit of data isolation, relatively less downtime for customers to access the platform  16 , and customer-driven upgrade schedules. An example of implementing a customer instance within a multi-instance cloud architecture will be discussed in more detail below with reference to  FIG. 2 . 
       FIG. 2  is a schematic diagram of an embodiment of a multi-instance cloud architecture  100  where embodiments of the present disclosure may operate.  FIG. 2  illustrates that the multi-instance cloud architecture  100  includes the client network  12  and the network  14  that connect to two (e.g., paired) data centers  18 A and  18 B that may be geographically separated from one another. Using  FIG. 2  as an example, network environment and service provider cloud infrastructure client instance  102  (also referred to herein as a client instance  102 ) is associated with (e.g., supported and enabled by) dedicated virtual servers (e.g., virtual servers  26 A,  26 B,  26 C, and  26 D) and dedicated database servers (e.g., virtual database servers  104 A and  104 B). Stated another way, the virtual servers  26 A- 26 D and virtual database servers  104 A and  104 B are not shared with other client instances and are specific to the respective client instance  102 . In the depicted example, to facilitate availability of the client instance  102 , the virtual servers  26 A- 26 D and virtual database servers  104 A and  104 B are allocated to two different data centers  18 A and  18 B so that one of the data centers  18  acts as a backup data center. Other embodiments of the multi-instance cloud architecture  100  could include other types of dedicated virtual servers, such as a web server. For example, the client instance  102  could be associated with (e.g., supported and enabled by) the dedicated virtual servers  26 A- 26 D, dedicated virtual database servers  104 A and  104 B, and additional dedicated virtual web servers (not shown in  FIG. 2 ). The client instance  102  may enable any suitable number of web portals  21 , mobile interfaces  22 , and/or any other suitable user interfaces that facilitate providing cloud computing services to client devices  20 . 
     Although  FIGS. 1 and 2  illustrate specific embodiments of a cloud computing system  10  and a multi-instance cloud architecture  100 , respectively, the disclosure is not limited to the specific embodiments illustrated in  FIGS. 1 and 2 . For instance, although  FIG. 1  illustrates that the platform  16  is implemented using data centers, other embodiments of the platform  16  are not limited to data centers and can utilize other types of remote network infrastructures. Moreover, other embodiments of the present disclosure may combine one or more different virtual servers into a single virtual server or, conversely, perform operations attributed to a single virtual server using multiple virtual servers. For instance, using  FIG. 2  as an example, the virtual servers  26 A,  26 B,  26 C,  26 D and virtual database servers  104 A,  104 B may be combined into a single virtual server. Moreover, the present approaches may be implemented in other architectures or configurations, including, but not limited to, multi-tenant architectures, generalized client/server implementations, and/or even on a single physical processor-based device configured to perform some or all of the operations discussed herein. Similarly, though virtual servers or machines may be referenced to facilitate discussion of an implementation, physical servers may instead be employed as appropriate. The use and discussion of  FIGS. 1 and 2  are only examples to facilitate ease of description and explanation and are not intended to limit the disclosure to the specific examples illustrated therein. 
     As may be appreciated, the respective architectures and frameworks discussed with respect to  FIGS. 1 and 2  incorporate computing systems of various types (e.g., servers, workstations, client devices, laptops, tablet computers, cellular telephones, and so forth) throughout. For the sake of completeness, a brief, high level overview of components typically found in such systems is provided. As may be appreciated, the present overview is intended to merely provide a high-level, generalized view of components typical in such computing systems and should not be viewed as limiting in terms of components discussed or omitted from discussion. 
     By way of background, it may be appreciated that the present approach may be implemented using one or more processor-based systems such as shown in  FIG. 3 . Likewise, applications and/or databases utilized in the present approach may be stored, employed, and/or maintained on such processor-based systems. As may be appreciated, such systems as shown in  FIG. 3  may be present in a distributed computing environment, a networked environment, or other multi-computer platform or architecture. Likewise, systems such as that shown in  FIG. 3 , may be used in supporting or communicating with one or more virtual environments or computational instances on which the present approach may be implemented. 
     With this in mind, an example computer system may include some or all of the computer components depicted in  FIG. 3 .  FIG. 3  generally illustrates a block diagram of example components of a computing system  200  and their potential interconnections or communication paths, such as along one or more busses. As illustrated, the computing system  200  may include various hardware components such as, but not limited to, one or more processors  202 , one or more busses  204 , memory  206 , input devices  208 , a power source  210 , a network interface  212 , a user interface  214 , and/or other computer components useful in performing the functions described herein. 
     The one or more processors  202  may include one or more microprocessors capable of performing instructions stored in the memory  206 . Additionally or alternatively, the one or more processors  202  may include application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), and/or other devices designed to perform some or all of the functions discussed herein without calling instructions from the memory  206 . 
     With respect to other components, the one or more busses  204  include suitable electrical channels to provide data and/or power between the various components of the computing system  200 . The memory  206  may include any tangible, non-transitory, and computer-readable storage media. Although shown as a single block in  FIG. 1 , the memory  206  can be implemented using multiple physical units of the same or different types in one or more physical locations. The input devices  208  correspond to structures to input data and/or commands to the one or more processors  202 . For example, the input devices  208  may include a mouse, touchpad, touchscreen, keyboard and the like. The power source  210  can be any suitable source for power of the various components of the computing system  200 , such as line power and/or a battery source. The network interface  212  includes one or more transceivers capable of communicating with other devices over one or more networks (e.g., a communication channel). The network interface  212  may provide a wired network interface or a wireless network interface. A user interface  214  may include a display that is configured to display text or images transferred to it from the one or more processors  202 . In addition and/or alternative to the display, the user interface  214  may include other devices for interfacing with a user, such as lights (e.g., LEDs), speakers, and the like. 
     With the preceding background discussion in mind,  FIG. 4  is a flowchart of a process  230  for providing search suggestions within a client instance  102  of  FIG. 2 , according to embodiments of the present disclosure. The process  230  may be implemented in the form of a software application that includes instructions executable by at least one suitable processor present in a device employed on the cloud computing system  10 . In particular, the process  230  may be performed on a device in communication with the client instance  102 , such as by a web browser application or portal  21  or mobile interface  22 . The illustrated process  230  is merely provided as an example, and in other embodiments, certain illustrated steps of the process  230  may be performed in other orders, skipped, or repeated, in accordance with the present disclosure. 
     As illustrated in process block  232 , a processor  202  receives a partial search query from a user, such as via a dynamic process by which a growing character string is provided as the partial search query input as a user enters a search. For example,  FIG. 5  is a perspective view of a web portal  21  providing search suggestions within a client instance  102  of  FIG. 2 , according to embodiments of the present disclosure. The web portal  21  includes a search field  260  in the form of a text box. A user has entered a partial search query  262  (e.g., “b”). The user may enter the partial search query  262  in the process of entering a full search query (e.g., “best practices documentation”). The web portal  21  may send the partial search query  262  to the processor  202 , and may send subsequent partial search queries  262  (e.g., “be”, “bes”, and so on) to the processor  202  as the user continues entering the search query. 
     Turning back to  FIG. 4 , in process block  234 , the processor  202  determines user-based search suggestions based on previous search queries performed by the user and the partial search query  262 . In particular, a memory or data store (e.g., database) in communication with the processor  202  may store previous search queries performed by the user (e.g., in the memory  206  or a database in communication with with the application). As such, the processor  202  may determine the previous search queries performed by the user that include the partial search query  262 . For example, the user may have performed the previous search query “best practices documentation”, and, accordingly, the processor  202  may determine that this previous search query is a user search suggestion because it includes the partial search query  262  “b”. 
     In process block  236 , the processor  202  also determines instance-based search suggestions based on previous search queries performed on the client instance  102  (which may be associated with a respective organization or enterprise or a department or other sub-unit within such an organization) and the partial search query  262 . In particular, the previous search queries performed on the instance  102  may include search queries performed by other users on the instance  102 . The processor  202  may store previous search queries performed by users on the instance  102  (e.g., in the memory  206  or a database in communication with the application on which the search is being performed). For example,  FIG. 6  is a perspective view of a web portal  21  listing previously performed search queries (e.g., search events) on the client instance  102  of  FIG. 2  in a table, according to embodiments of the present disclosure. As illustrated, the table  263  includes the previously performed search queries  264 , the number of results  265  returned from the search query  264 , the user  266  performing the search query  264 , and search context information  267  associated with the search query  264  (e.g., identification of the software application at which the search query  264  was entered). It should be understood, any suitable metric or information may be stored in the table  263  associated with each previously performed search query  264 . 
     In some embodiments, the processor  202  may generate search suggestions (including the user-based search suggestions and the instance-based search suggestions) based on, for example, the table  263  of previously performed search queries in  FIG. 6 . For example,  FIG. 7  is a perspective view of a web portal  21  listing search suggestions in a table that were generated based on search queries previously performed on the client instance  102  of  FIG. 2 , according to embodiments of the present disclosure. As illustrated, the table  268  includes the search suggestion  269 , search context information  270  associated with the search suggestion  269  (e.g., identification of the software application at which the search suggestion  269  was entered), a user group  271  that performed the search suggestion  269 , and score  272  of the search suggestion  269 . The score  272  may be any suitable metric used to indicate a relevancy of the search suggestion  269 . For example, the processor  202  may generate the score  272  of a search suggestion  269  based on frequency of the search suggestion  269  being performed, recency or how recently the search suggestion  269  was last performed, frequency of the search suggestion  269  being performed in a recent period of time (e.g., to determine how the search suggestion  269  trending), and so on. Any suitable period of time may be used to determine whether the search suggestion  269  is trending, such as determining the number of times the search suggestion  269  was performed in the last day, week, month, six months, year, five years, and so on. It should be understood, any suitable metric or information may be stored in the table  268  associated with each search suggestion  269 . 
     In some cases, the processor  202  may generate the search suggestions  269  in the table  268  of  FIG. 7 , and determine the user search suggestions (in process block  234 ) by filtering the table  268  based on the user. 
     As such, the processor  202  may determine the previous search queries performed on the client instance  102  that include the partial search query  262 . For example, the previous search queries performed on the client instance  102  may include the search query “best colors for office”, and, accordingly, the processor  202  may determine that this previous search query is an instance search suggestion because it includes the partial search query  262  “b”. 
     In some embodiments, the processor  202  may ensure that the search suggestions do not include those that have blacklisted terms. That is, certain terms may be prohibited due to a variety of reasons, such as suitability, security, confidentiality and so on. The processor  202  may store the blacklisted terms (e.g., in the memory  206  or other suitable data store). In some cases, the blacklisted terms may include blacklisted formats that are associated with terms that may be prohibited. For example, a blacklisted format may include three numbers, followed by a hyphen, followed by two numbers, followed by a hyphen, followed by four numbers (e.g., “XXX-XX-XXXX”) because this format is associated with social security numbers which may be prohibited for security and/or confidentiality reasons.  FIG. 8  is a perspective view of a web portal  21  listing blacklisted terms in a table, according to embodiments of the present disclosure. The table  273  includes the blacklisted term “blacklist”  274 , as well as details of the blacklisted term. For example, the blacklisted term “blacklist”  274  is active (as indicated by the “true” value  275 ) and is part of the English language (as indicated by the “en” value  276 ). 
     As such, and turning back to  FIG. 4 , in decision block  238 , the processor  202  determines whether any of the search suggestions contain a blacklisted term (e.g.,  274 ). If so, the processor  202  removes the blacklisted search suggestion(s), such that the blacklisted search suggestions may not be provided, displayed, or otherwise enabled to be viewed and/or selected by the user. 
     In process block  242 , the processor  202  receives one or more instance filter criteria. The instance filter criteria may include any suitable criteria used to filter the instance search suggestions to generate more relevant search suggestions for the user. For example, the instance filter criteria may be associated with the interface (e.g., mobile or web portal) used by the user. As illustrated in  FIG. 5 , the interface used by the user is a web portal  21 . As such, the instance filter criteria may include search queries that were performed on a web portal  21  interface. In some cases, the interface may be, for example, a mobile interface  22 . For example,  FIG. 9  is a perspective view of a mobile interface  22  providing search suggestions within a client instance  102  of  FIG. 2 , according to embodiments of the present disclosure. In such a case, the instance filter criteria may include search queries that were performed on a mobile interface  22 . In this manner, the processor  202  may filter the instance search suggestions using the instance filter criteria to generate search suggestions relevant to the user&#39;s interface. 
     In additional or alternative embodiments, the instance filter criteria may be associated with a search context (e.g., associated with a software application or page at which the search query is entered). For example, the web portal  21  of  FIG. 5  may be able to provide, enable access to, or execute multiple software applications, including a knowledge base application. In such an example, the search field  260  of the web portal  21  of  FIG. 5  may be displayed or provided as part of the knowledge base application. As such, the instance filter criteria may include search queries that were performed and/or entered search fields  260  that were provided or displayed as part of the knowledge base application. As another example, the mobile interface  22  of  FIG. 9  may be able to provide, enable access to, or execute multiple software applications, including a catalog application. In such an example, the search field  260  of the mobile interface  22  of  FIG. 9  may be displayed or provided as part of the catalog application. As such, the instance filter criteria may include search queries that were performed and/or entered search fields  260  that were provided or displayed as part of the catalog application. In this manner, the processor  202  may filter the instance search suggestions using the instance filter criteria to generate search suggestions relevant to the user&#39;s search context. 
     The instance filter criteria may also or alternatively be associated with a user group (e.g., a company, organization, department, regional office, location, user role, and so on) that the user belongs to. For example, the user may be an employee at a certain company. As such, the instance filter criteria may include search queries that were performed by other users of the same company. As another example, the user may have a role (e.g., as defined by the client instance  102 ) as a system administrator. As such, the instance filter criteria may include search queries that were performed by other users having the role of system administrator. In this manner, the processor  202  may filter the instance search suggestions using the instance filter criteria to generate search suggestions relevant to the user&#39;s role. 
     In some cases, the client instance  102  may include multiple domains, such that the client instance  102  may provide different services on each domain. As such, the client instance  102  may provide a first service to users of a first domain, and a second service to users of a first domain. In such multi-domain instances, data of one domain may not be accessible to users of another domain, and vice versa. In such cases, the instance filter criteria may be associated with the domain at which the search query was performed. For example, in  FIG. 5 , the user may be performing a search query in the web portal  21  of a first domain of a client instance  102 , which includes multiple domains. That is, the partial search query  262  received in process block  232  was entered in the first domain. As such, the instance filter criteria may include search queries that were performed in the first domain of the instance  102 . In this manner, the processor  202  may filter the instance search suggestions using the instance filter criteria to generate search suggestions relevant to the user&#39;s domain. 
     Turning back to  FIG. 4 , in process block  244 , the processor  202  filters the instance search suggestions based on the one or more instance filter criteria. That is, the processor  202  may remove any instance search suggestions that do not meet the instance filter criteria. For example, if the instance filter criteria includes search queries that were performed on a web portal  21 , then the processor  202  may remove any instance search suggestions that were not performed on the web portal  21 . 
     In process block  246 , the processor  202  receives one or more ranking criteria. The ranking criteria may be any suitable criteria used to rank the search suggestions, such as frequency of the search queries being performed, recency or how recently the search queries were last performed, frequency of the search queries being performed in a recent period of time (e.g., to determine what search queries are currently trending), and so on. Any suitable period of time may be used to determine what search queries are currently trending, such as determining the search queries performed in the last day, week, month, six months, year, five years, and so on. In some embodiments, the ranking criteria may include the instance filter criteria received in process block  242 . 
     In process block  248 , the processor  202  ranks the user search suggestions based on the one or more ranking criteria. For example, if the ranking criteria includes the frequency of the search queries being performed, then the processor  202  ranks the user search suggestions based on the frequency of each search suggestion being performed. 
     In process block  250 , the processor  202  ranks the instance search suggestions based on the one or more ranking criteria. For example, if the ranking criteria includes the frequency of the search queries being performed in a recent period of time (e.g., in a recent period of time), then the processor  202  ranks the instance search suggestions based on the frequency of each search suggestion being performed in the recent period of time. While the processor  202  is described as ranking the user search suggestions and the instance search suggestions using the same ranking criteria, it should be understood that different ranking criteria may be used to rank the user search suggestions when compared to ranking the instance search suggestions. For example, in some embodiments, the ranking criteria may include the instance filter criteria received in process block  242 . As such, the processor  202  may rank the instance search suggestions based on, for example, whether the instance search suggestions have the same search context as the partial search query  262  received in process block  242 . As illustrated in  FIG. 7 , the processor  202  may generate a score  272  of each search suggestion  269  based on, for example, the ranking criteria. The processor  202  may then sort the search suggestions  269  by the score  272  to rank the search suggestions  269 . 
     In process block  252 , the processor  202  enables the user to select the user-based search suggestions and the instance search suggestions that meet or exceed a threshold. In particular, the processor  202  may determine those user search suggestions that meet or exceed a threshold and those instance-based search suggestions that meet or exceed a threshold. The thresholds may include any suitable threshold used to display or provide a reasonable number of search suggestions to the user. The threshold used to evaluate the user search suggestions may be the same or different than the threshold used to evaluate the instance search suggestions. For example, the threshold may include the top two ranked user search suggestions and the top two ranked instance search suggestions. As such, the processor  202  may enable the user to select the top two ranked user search suggestions and the top two ranked instance search suggestions. As another example, the threshold may include the top two ranked user search suggestions and the top one percent of ranked instance search suggestions. As such, the processor  202  may enable the user to select the top two ranked user search suggestions and the top one percent of ranked instance search suggestions. 
     The processor  202  may enable the user to select the user search suggestions and the instance search suggestions by displaying or providing the search suggestions in a drop down list or menu and performing a search using the search suggestion when the search suggestion is selected by the user. For example, in  FIG. 5 , the processor  202  enables the user to select the user search suggestions and the instance search suggestions that meet or exceed a threshold by displaying the user search suggestions  282  and the instance search suggestions  284  in the drop down menu  286 . In some embodiments, the processor  202  may indicate which search suggestions are user search suggestions  282  and which search suggestions are instance search suggestions  284 . As illustrated, the processor  202  provides an indication  288  (e.g., a visual indication) of the user search suggestions  282  in the form of a graphical clock, and an indication  290  (e.g., a visual indication) of the instance search suggestions  284  in the form of a graphical magnifying glass. Advantageously, the process  230  enables a first time user of the web portal  21  and/or the mobile interface  22  to receive search suggestions (e.g., via the instance search suggestions) even if the user has not performed a previous search query. In this manner, the process  230  may provide relevant search suggestions  282 ,  284  to the user without the user having to enter a full search query, saving time and providing a better user experience. 
     The example search suggestions shown in  FIG. 5  may be for a user who has a role of a system administrator. As such, the search suggestions  282 ,  284  displayed in the drop down menu  286  may include user search suggestions  282  that were previous search queries performed by the user and instance search suggestions  284  that previous search queries performed on the instance  102  by other users that had roles as system administrators. As another example,  FIG. 10  is a perspective view of a web portal  21  providing search suggestions within a client instance  102  of  FIG. 2  for a user that does not have a role as system administrator, according to embodiments of the present disclosure. As such, the instance filter criteria used to generate the instance search suggestions  284  may include search queries that were performed by other users having the same role as the user, or the instance filter criteria may not include a user role. 
     In some embodiments, the client interface  102  may include the capability of disabling having search queries contribute to search suggestions. For example, a system administrator may search for a legacy component, but may desire that the search query not contribute to future search suggestions to avoid having other users attempt to install or purchase the legacy component. As such, the system administrator may disable having his search query contribute to search suggestions. 
     The specific embodiments described above have been shown by way of example, and it should be understood that these embodiments may be susceptible to various modifications and alternative forms. It should be further understood that the claims are not intended to be limited to the particular forms disclosed, but rather to cover all modifications, equivalents, and alternatives falling within the spirit and scope of this disclosure. 
     The techniques presented and claimed herein are referenced and applied to material objects and concrete examples of a practical nature that demonstrably improve the present technical field and, as such, are not abstract, intangible or purely theoretical. Further, if any claims appended to the end of this specification contain one or more elements designated as “means for [perform]ing [a function]. . .” or “step for [perform]ing [a function]. . . ”, it is intended that such elements are to be interpreted under 35 U.S.C. 112(f). However, for any claims containing elements designated in any other manner, it is intended that such elements are not to be interpreted under 35 U.S.C. 112(f).