Patent Application
20140372864
Websites often contain a significant amount of content. For example, websites corresponding to social networks are typically built around a vast feed of content that serves as the primary experience for most users. In interest networks (which include standard forum sites), the sites tend to be divided into interests or topical message boards. Such divisions encourage ‘siloed’ consumption and engagement with the content, and hinder discovery of additional content and/or people of interest.
Most users do not interact with much of the content that they might otherwise find interesting. For example, many websites are arranged as a single linear (e.g., in one or more columns) feed of posts, which does not help a user discover other facets of the network. Indeed, many people typically browse the first feed they see (often the “everyone” or “everything” feed). As a result, it is very possible that a user will never discover the rich content that the rest of the site has to offer.
Because users tend to stay in the first feed they find and not explore the rest of the site, they may also fail to find other areas of the site that otherwise would be interesting to them, or areas that would allow them to customize or enrich their experience in the primary feed. For example, forms in which users describe their areas of interests (or non-interest) may be located on a settings page that many users fail to find.
Some sites have separate static sections or headers that present the most globally popular sections on the site. A “hub” may be provided to guide site navigation. While useful, such solutions still suffer from requiring explicit, somewhat exploratory navigation by the user in order to engage with these other sections.
This Summary is provided to introduce a selection of representative concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used in any way that would limit the scope of the claimed subject matter.
Briefly, various aspects of the subject matter described herein are directed towards outputting (e.g., presenting) opportunity cards to a user based upon the user's profile data, in which the opportunity cards provide a mechanism for the user to access other website content that is likely of interest to the user and/or receive information or an action to take regarding the website that is likely of interest to the user. One or more aspects are directed towards generating opportunity cards for a user based upon user-profile information, including searching for content and/or information related to a website. A set of opportunity cards may be generated based on a user's interests. The opportunity cards are filtered into a subset of opportunity cards that the user is likely to be interested in, and one or more of the opportunity cards are output from the subset for viewing by the user. Opportunity cards also may be created in the absence of (or in addition to) specific user information, based upon, for example, averaged or otherwise combined user interests, other users' behavior, trending topics, or popular users.
In one or more aspects, a website including a plurality of web servers is coupled to a data store that includes content and user profile data, in which the website includes an opportunity card generation and selection mechanism (e.g., algorithm). The opportunity card generation and selection mechanism is configured to request a search the content based upon the user profile data for a user and/or information about other (e.g., typical) users, and to generate opportunity cards for the user based upon results of the search. The mechanism selects opportunity cards to present to the user in conjunction with other rendered content.
One or more aspects are directed towards generating opportunity cards to present to a user from a website, in which the opportunity cards relate to other content in the website, and in which at least some of the opportunity cards provide links to the other content. One or more of the opportunity cards may be presented inline with a stream of content presented to the user, with an action taken based upon user interaction with an opportunity card.
The present invention is illustrated by way of example and not limited in the accompanying figures in which like reference numerals indicate similar elements and in which:
Various aspects of the technology described herein are generally directed towards generating and outputting opportunity cards (or simply “opportunities”), comprising one or more selected links and/or informational notifications related to a website. The opportunity cards may be generated based upon a user's profile, and may be output/presented in various ways, including interspersed inline among a stream of posts or otherwise associated with a stream of posts.
Opportunity cards may be generated for dynamically generated streams (e.g. related posts to a single post or searched by topic of interest) as well as existing, static streams. For example, a user may provide profile data that causes a stream to be dynamically generated when the user initially logs on, and/or a user may interact to select or search during a session, such as with respect to a topic of interest, and have a stream dynamically generated based upon the search results. Opportunity cards may be generated and/or selected for such streams.
More particularly, in one or more implementations, in addition to an “everyone” feed, the website system has the capability of dynamically generating feeds of posts. For example, given an interesting post in the everyone feed, a user can click that post to explore a series of related posts. Within that dynamically generated related post feed, the system may generate “opportunity cards” that enumerate some of the people, collections of interests, and/or activities that the system thinks the user will find the most interesting. These opportunity cards may be mixed in with the feed of posts, integrating naturally with the flow of browsing the site's content, and allowing the user to take action on these opportunities as part of their browsing and consuming experience. In addition, these opportunity cards provide links to explore the results of queries representing segments of the site's content that have been dynamically curated, rather than provided by users.
In general, opportunity cards may suggest and provide straightforward access to content or content sources (e.g., other users) to help users increase their engagement in a community, improve connections (e.g., expand social graphs), and discover additional content of interest (e.g., collections), without dedicated hubs, for example. Via opportunity cards, a user may see feeds of content generated dynamically for deeper exploration of a user's interest, and/or may be offered guidance based on past interactions with the site, new features of the site, and so on.
It should be understood that any of the examples herein are non-limiting. For example, opportunity cards may be presented with site content, however the technology described herein is not limited to such presentation. For example, an opportunity card may be emailed and/or output via a notification sent to a device, possibly not the same device that the user typically uses to access the site with which the opportunity card is associated. As such, the present invention is not limited to any particular embodiments, aspects, concepts, structures, functionalities or examples described herein. Rather, any of the embodiments, aspects, concepts, structures, functionalities or examples described herein are non-limiting, and the present invention may be used various ways that provide benefits and advantages in computing, networking and providing content in general.
As one example, a user who has registered an interest in classic cars may initially see posts related to classic cars. The user receives an interactive web page 110 containing the selected content. For example, the selected content may be arranged as a plurality of posts, arranged in time order, through which the user can scroll. In general, posts comprise images and accompanying text, possibly including comments, assembled and uploaded by various contributors to the website. For purposes of explanation herein, posts are used in the examples, however it is understood that opportunity cards are not limited to content in the form of posts.
As described herein, the interactive web page 110 includes one or more opportunity cards 112 that are generated for the user based upon the user profile data. Unlike conventional content, the opportunity cards are automatically generated and selected (block 114) for the user to provide information related to enhancing the user's experience with the site.
By way of example, an opportunity card may be generated to inform a user that a new collection (e.g., of posts) has been added to the site, providing the user with an opportunity to interact with the new collection. Such an opportunity card may be selected for the user based upon other topics in which the user is interested, e.g., “cats,” which may be determined by keyword matching other such techniques. Another opportunity card presented to a user may be based upon a person that the user follows, e.g., a friend, or a friend of a friend, (e.g., “Joe added a new collection” or “Jane added content to a collection”). Another opportunity card may be generated from keywords, current interests or activities of the user and so on, e.g., the user may be offered similar content to some content the user is currently following. An opportunity card need not be related to content or people, but instead may be informational, e.g., to inform the user of some new feature or change to the site that the user otherwise may not see.
As generally represented in
The opportunity cards may generally look like other posts, or may be intentionally designed to be visually different in some way from other posts to easily differentiate (e.g., call attention to) them. An opportunity card may be rendered at the top of each “virtual” page of results in a “posts” view that shows the posts. Instead of (or in addition to) inline opportunity cards, as represented in
As represented in
By way of example, “Jahan” in the text of the opportunity card 440(1) may be a hoverable and clickable link. Clicking this opportunity takes the user to content (e.g., posts) associated with the user named Jahan. The user may also click “post” to see the particular newly added post. The link “My Art Gallery” is clickable and navigates to a corresponding collection named as such.
A user thus may elect to jump to the new content via an opportunity action in an opportunity card. Alternatively, another action that the user may take is to select “Follow” within the opportunity card, whereby the user stays at the current set of content (e.g., the current location in the stream) but has the posts (e.g., the collection) identified in the opportunity card added to the current stream for the user to scroll to when desired. Note that in the opportunity card 440(2) the button 442 has changed from “Follow” to “Following” to indicate that the user already elected to follow that opportunity; although the button text in
To give users opportunity cards that are likely relevant to the user while avoiding repetition, opportunity card options in one implementation are chosen based on weighted random chance. There are different types of opportunities, and each type of opportunity may have a weight corresponding to a specific configurable percentage chance that the type will be chosen. This chance can be overridden or reweighted by detected user behavior; (e.g., a user who has been interested in “hot dog” posts today may be given an opportunity card asking the user whether he or she “would like to follow the hot dog collection”).
Opportunities can also be chosen based on implied data from the user's recent behavior (the one being shown an opportunity). By way of example, if a user buys a barbecue and starts interacting with related content (as the user has just started that interest), the system may create and highly prioritize an opportunity or set of opportunities that directed the user to barbecue related posts, users, and collections. In other words, this is “inferred” data about the user profile based on behavior rather than “explicit” data. Moreover, the behavior may be obtained from another source, e.g., a shopping website may provide information about a recent user purchase, which may then be used in generating an opportunity card.
Thus, there are different types of opportunities, and each may be weighted differently. The following table exemplifies some possible types and rules and weights related thereto; it is understood that the table entries are only examples, and that not all exemplified types may be present in a given implementation, and/or that other types may be added:
As can be seen from the example table, some of the types have rules that need to be met before an opportunity card will be generated. For example, some of the rules include that any new recommended collections need to be actually new (within the last seven days) and not already followed by the user. A “collection” needs to have at least three posts to be considered a collection. Contributions to an existing, followed collection need to be recent, e.g., made within the last 24 hours of the session; e.g., a collection recommended because of popularity also needs to be current, e.g., there may be many formerly popular collections regarding the 2012 London Olympic games, but the popularity has waned over time and thus such a collection is not current. Other example rules may be seen in the table. It is understood that the values (e.g., timeframes, number of posts, and so on) that a rule evaluates are only examples, and that these values may be tweaked and/or learned for a given implementation.
Each of the types has a weight that will be a factor in how frequently that type of opportunity appears. The weights generally attempt to bias the types to those a user is likely more interested in seeing, while giving likely less interesting ones some visibility. In one or more implementations, the user may configure some of the weights per-user preferences, e.g., those that are not globally weighted, with per-user weights maintained as part of the user profile data, for example. It is understood that the above table entries including the weights therein are only examples, and that different values and the like may be used, e.g., learned through user feedback, such as how often each type of opportunity card is clicked.
Scoring of collections of interests may be done by an activity rank measure. Opportunity card recommendations can be made based on secondary shared attributes, such as tags on collections of interests as well as intersections of user behaviors/likes/shared interests/follows. Opportunity card recommendations also may be based on things the user has not done yet, such as adding personal information, selecting general areas of interest, and/or providing contact information for other social sites.
With respect to each opportunity card type, a selection process attempts to prepare a variety of results that avoids repetition of the same opportunities (suggestions) over and over again to the user within a given session. A session may be time-based, based upon login and logout, or some other criteria (e.g., three logins and logouts). To avoid repetition, the selection process may choose randomly within the set of values for a given opportunity.
Note that each time a person adds a post to a collection, a different opportunity card may be generated, e.g., “Jahan added a post to the collection” (as in
Different algorithms may be used to search for the opportunities/cards, such as for different search criteria and different types of opportunities. As a result, there may be duplicates. Duplicate detection, e.g., via a hash of the content or part thereof may be used to eliminate duplicates (step 510). A dictionary of {hash value, corresponding opportunity card content} entries or the like may be maintained and access for this purpose.
From this set of opportunities/cards, as represented via steps 512 and 514, the process may filter the set (e.g., to determine which fifty or so are the most appropriate for the user) into a subset that may be ranked and/or ordered. This may be based upon various filtering criteria, such as to recommend a new collection from someone the user knows, recommend a collection in an area of interest of the user, recommend a new user to the system who the use knows otherwise (e.g., a friend on another social network), follow a person who has common interests with the user, follow a person whom a friend (or someone the user follows) has just decided to follow, and so on.
From this reduced subset, at step 516 some number N (e.g., 3) of opportunity cards may be selected and mixed into or otherwise associated with the content for the user, e.g., interspersed into the stream of posts a user is about to have rendered for viewing (step 518). The subset is maintained so that more opportunity cards are available as needed during the session, e.g., as represented by step 520.
Note that opportunity cards need not be generated during a session as in
As can be seen, opportunity cards provide a straightforward natural way to increase connections among members and help users discover topics of interest. Other benefits of opportunity cards include a way to notify a user of a missed activity, and to encourage activities that may increase the value of the site for the user.
One of ordinary skill in the art can appreciate that the various embodiments and methods described herein can be implemented in connection with any computer machine or other client or server device, which can be deployed as part of a computer network or in a distributed computing environment, and can be connected to any kind of data store or stores. In this regard, the various embodiments described herein can be implemented in any computer system or environment having any number of memory or storage units, and any number of applications and processes occurring across any number of storage units. This includes, but is not limited to, an environment with server computers and client computers deployed in a network environment or a distributed computing environment, having remote or local storage.
Distributed computing provides sharing of computer resources and services by communicative exchange among computing devices and systems. These resources and services include the exchange of information, cache storage and disk storage for objects, such as files. These resources and services also include the sharing of processing power across multiple processing units for load balancing, expansion of resources, specialization of processing, and the like. Distributed computing takes advantage of network connectivity, allowing clients to leverage their collective power to benefit the entire enterprise. In this regard, a variety of devices may have applications, objects or resources that may participate in the resource management mechanisms as described for various embodiments of the subject disclosure.
Each computing object 610, 612, etc. and computing objects or devices 620, 622, 624, 626, 628, etc. can communicate with one or more other computing objects 610, 612, etc. and computing objects or devices 620, 622, 624, 626, 628, etc. by way of the communications network 640, either directly or indirectly. Even though illustrated as a single element in
There are a variety of systems, components, and network configurations that support distributed computing environments. For example, computing systems can be connected together by wired or wireless systems, by local networks or widely distributed networks. Currently, many networks are coupled to the Internet, which provides an infrastructure for widely distributed computing and encompasses many different networks, though any network infrastructure can be used for example communications made incident to the systems as described in various embodiments.
Thus, a host of network topologies and network infrastructures, such as client/server, peer-to-peer, or hybrid architectures, can be utilized. The “client” is a member of a class or group that uses the services of another class or group to which it is not related. A client can be a process, e.g., roughly a set of instructions or tasks, that requests a service provided by another program or process. The client process utilizes the requested service without having to “know” any working details about the other program or the service itself.
In a client/server architecture, particularly a networked system, a client is usually a computer that accesses shared network resources provided by another computer, e.g., a server. In the illustration of
A server is typically a remote computer system accessible over a remote or local network, such as the Internet or wireless network infrastructures. The client process may be active in a first computer system, and the server process may be active in a second computer system, communicating with one another over a communications medium, thus providing distributed functionality and allowing multiple clients to take advantage of the information-gathering capabilities of the server.
In a network environment in which the communications network 640 or bus is the Internet, for example, the computing objects 610, 612, etc. can be Web servers with which other computing objects or devices 620, 622, 624, 626, 628, etc. communicate via any of a number of known protocols, such as the hypertext transfer protocol (HTTP). Computing objects 610, 612, etc. acting as servers may also serve as clients, e.g., computing objects or devices 620, 622, 624, 626, 628, etc., as may be characteristic of a distributed computing environment.
As mentioned, advantageously, the techniques described herein can be applied to any device. It can be understood, therefore, that handheld, portable and other computing devices and computing objects of all kinds are contemplated for use in connection with the various embodiments. Accordingly, the below general purpose remote computer described below in
Embodiments can partly be implemented via an operating system, for use by a developer of services for a device or object, and/or included within application software that operates to perform one or more functional aspects of the various embodiments described herein. Software may be described in the general context of computer executable instructions, such as program modules, being executed by one or more computers, such as client workstations, servers or other devices. Those skilled in the art will appreciate that computer systems have a variety of configurations and protocols that can be used to communicate data, and thus, no particular configuration or protocol is considered limiting.
With reference to
Computer 710 typically includes a variety of computer readable media and can be any available media that can be accessed by computer 710. The system memory 730 may include computer storage media in the form of volatile and/or nonvolatile memory such as read only memory (ROM) and/or random access memory (RAM). By way of example, and not limitation, system memory 730 may also include an operating system, application programs, other program modules, and program data.
A user can enter commands and information into the computer 710 through input devices 740. A monitor or other type of display device is also connected to the system bus 722 via an interface, such as output interface 750. In addition to a monitor, computers can also include other peripheral output devices such as speakers and a printer, which may be connected through output interface 750.
The computer 710 may operate in a networked or distributed environment using logical connections to one or more other remote computers, such as remote computer 770. The remote computer 770 may be a personal computer, a server, a router, a network PC, a peer device or other common network node, or any other remote media consumption or transmission device, and may include any or all of the elements described above relative to the computer 710. The logical connections depicted in
As mentioned above, while example embodiments have been described in connection with various computing devices and network architectures, the underlying concepts may be applied to any network system and any computing device or system in which it is desirable to improve efficiency of resource usage.
Also, there are multiple ways to implement the same or similar functionality, e.g., an appropriate API, tool kit, driver code, operating system, control, standalone or downloadable software object, etc. which enables applications and services to take advantage of the techniques provided herein. Thus, embodiments herein are contemplated from the standpoint of an API (or other software object), as well as from a software or hardware object that implements one or more embodiments as described herein. Thus, various embodiments described herein can have aspects that are wholly in hardware, partly in hardware and partly in software, as well as in software.
The word “exemplary” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used, for the avoidance of doubt, such terms are intended to be inclusive in a manner similar to the term “comprising” as an open transition word without precluding any additional or other elements when employed in a claim.
As mentioned, the various techniques described herein may be implemented in connection with hardware or software or, where appropriate, with a combination of both. As used herein, the terms “component,” “module,” “system” and the like are likewise intended to refer to a computer-related entity, either hardware, a combination of hardware and software, software, or software in execution. For example, a component may be, but is not limited to being, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of illustration, both an application running on computer and the computer can be a component. One or more components may reside within a process and/or thread of execution and a component may be localized on one computer and/or distributed between two or more computers.
The aforementioned systems have been described with respect to interaction between several components. It can be appreciated that such systems and components can include those components or specified sub-components, some of the specified components or sub-components, and/or additional components, and according to various permutations and combinations of the foregoing. Sub-components can also be implemented as components communicatively coupled to other components rather than included within parent components (hierarchical). Additionally, it can be noted that one or more components may be combined into a single component providing aggregate functionality or divided into several separate sub-components, and that any one or more middle layers, such as a management layer, may be provided to communicatively couple to such sub-components in order to provide integrated functionality. Any components described herein may also interact with one or more other components not specifically described herein but generally known by those of skill in the art.
In view of the example systems described herein, methodologies that may be implemented in accordance with the described subject matter can also be appreciated with reference to the flowcharts of the various figures. While for purposes of simplicity of explanation, the methodologies are shown and described as a series of blocks, it is to be understood and appreciated that the various embodiments are not limited by the order of the blocks, as some blocks may occur in different orders and/or concurrently with other blocks from what is depicted and described herein. Where non-sequential, or branched, flow is illustrated via flowchart, it can be appreciated that various other branches, flow paths, and orders of the blocks, may be implemented which achieve the same or a similar result. Moreover, some illustrated blocks are optional in implementing the methodologies described hereinafter.
While the invention is susceptible to various modifications and alternative constructions, certain illustrated embodiments thereof are shown in the drawings and have been described above in detail. It should be understood, however, that there is no intention to limit the invention to the specific forms disclosed, but on the contrary, the intention is to cover all modifications, alternative constructions, and equivalents falling within the spirit and scope of the invention.
In addition to the various embodiments described herein, it is to be understood that other similar embodiments can be used or modifications and additions can be made to the described embodiment(s) for performing the same or equivalent function of the corresponding embodiment(s) without deviating therefrom. Still further, multiple processing chips or multiple devices can share the performance of one or more functions described herein, and similarly, storage can be effected across a plurality of devices. Accordingly, the invention is not to be limited to any single embodiment, but rather is to be construed in breadth, spirit and scope in accordance with the appended claims.
