Patent Application
20140359009
Computer-based social networks can facilitate social interactions among users via the Internet or other types of computer networks. Using such social networks, users may build and maintain social relations with others who share similar interests, activities, backgrounds, or real-life connections. Users may also share with one another comments, stories, news, events, pictures, videos, and/or other types of content.
This Summary is provided to introduce a selection of 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 to limit the scope of the claimed subject matter.
In computer-based social networks, users can produce and/or consume various types of content available on social network servers. Retrieving, storing, and cataloging such content in whole may be difficult as the number of users increases to millions, tens of millions, or even billions.
Several embodiments of the present technology provide certain approaches to prioritize retrieval of published content from social network servers based on one or more factors indicative of a likelihood of content consumption. For example, in certain embodiments, the present technology can determine priority ratings of content produced by users based on social connections or social interactions of the users on social networks, usage of the social network services by the users, and/or a type, length, or other characteristics of published content. In other examples, the present technology may also retrieve content from social network servers according to one or more behaviors of the social network servers to streamline the retrieval process. Thus, relevant, popular, and/or useful content from social networks may be efficiently and timely retrieved, stored, and cataloged for ready consumption by other users.
Various embodiments of systems, devices, components, modules, routines, and processes for prioritized content retrieval from social network servers are described below. In the following description, example software codes, values, and other specific details are included to provide a thorough understanding of various embodiments of the present technology. A person skilled in the relevant art will also understand that the technology may have additional embodiments. The technology may also be practiced without several of the details of the embodiments described below with reference to
As used herein, the term “content” generally refers to information expressed in writing, speech, photos, video recording, or any other forms of media. Also used herein, the term “social network” generally refers to a community of people, organizations, or other entities who/that communicate with one another via a computer network (e.g., the Internet), a web-site (e.g., Facebook.com), an online service (e.g., Bing Social), or other types of social network services. For example, a social network on Facebook.com may include a user and his/her friends or all users registered with Facebook.com. In another example, a social network can also include a Facebook page (e.g., Healthy Diet and Lifestyle News) and users who read, comment, like, re-post, and/or otherwise interact with the Facebook page.
With computer-based social networks, users can share with one another various types of content. Thus, users can produce and/or consume content when interacting with one another. Efficiently and timely retrieving, storing, and/or cataloging user produced content on social networks in whole may be a challenge because users can produce a large amount of content. Several embodiments of the present technology can analyze profiles of users, content produced and/or liked by users, relationships of users with one another, and/or other social network information. Based on the analysis, several embodiments of the present technology can prioritize retrieval of such content so that relevant, popular, and/or useful content may be acquired in a timely, efficient, and effective fashion. The retrieved content can then be readily consumed or accessed by users via a search engine or other suitable components.
The social network server 120 can be configured to provide computer-based social network services to users. For example, in one embodiment, the social network server 120 can include a web server configured to facilitate social interactions among users in social networks via the computer network 140. In another embodiment, the social network server 120 can also include an administrative server configured to facilitate user registration, account management, and/or other function. In further embodiments, the social network server 120 can also include a mail server, an application server, a communication server, and/or other suitable types of server.
As shown in
The content 124 can include records of various types of content individual users of the social network services publish, link, re-post, and/or otherwise expose to other users of his/her social networks. For example, the content 124 can include photos, videos, status, or comments uploaded by users to the social network server 120. The content 124 can also include a link (e.g., a web address) posted by users to the social network server 120. The link can be associated with a news article, story, video clip, document, or other media. In further examples, the content 124 can include other suitable types of information.
The user device 110 can include a social network interface 112 configured to facilitate accessing the social network server 120 by a user (not shown). The user device 110 can include a desktop, a laptop, a tablet, a smartphone, and/or other suitable types of computing device. In one embodiment, the social network interface 112 can include a web browser-based interface (e.g., a web page). In other embodiments, the social network interface 112 can include an application-based interface, a text interface, or other suitable types of interface.
Via the social network interface 112, a user can conduct various social interactions with other users of the social network services. For example, the user can view a status of friends, read comments by friends, access photos, videos, or other types of media posted by friends, see activities of friends, and/or receive other suitable information from friends. In another example, the user can also post a comment to friends, upload photos, videos, or other types of media to be viewed by friends, post a link to a story, article, or other document, and/or otherwise communicate with friends and/or non-friends.
The content server 102 can be configured to selectively retrieve, store, and catalog content 124 maintained in the social network server 120. As shown in
In certain embodiments, the policy component 104 can be configured to receive the social network information 122 from the retrieval component 108. In other embodiments, the policy component 104 can be configured to compute or infer user interactions (e.g., likes, tags, comments, etc.) or other information from the content 124. In further embodiments, the policy component 104 can also be configured to compute or infer user activities or other information from the user device 110 based on, for example, search history (e.g., using a search engine), advertisement impressions, currently active users, and/or other data on the user device 110.
The policy component 104 can then generate a plurality of priority ratings 106 (e.g., as numerical scores) for the individual users of the social network services based on the received and/or inferred information and/or other suitable information. For example, the policy component 104 can assign the policy ratings 106 for a particular user based on the user's social connections or social interactions with others in his/her social networks, usage of the social network services by the user, and/or the user's published content on the social network server 120. In certain embodiments, a user associated with the user device 110 may provide a token 114 to the content server 102 to authorize access to the social network information 122 and/or the content 124. In another embodiment, the user may authorize access to the social network information 122 and/or the content 124 by registering with the content server 102 and/or in other suitable manners. In other embodiments, such a token 114 may be omitted. Based on the generated plurality of priority ratings 106, the policy component 104 can prioritize content retrieval, crawling, and/or indexing from the social network server 120, for example, by forming a prioritized retrieval list 107 for records identifying the individual users (referred to herein as “user records”) based on the priority ratings 106 and/or other suitable parameters. The user records can include at least one of a user name, email address, home/work address, telephone number, user identification number, and/or other suitable information. Embodiments of the policy component 104 are described in more detail below with reference to
The retrieval component 108 can then retrieve at least a portion of the content 124 from the social network server 120 based on the prioritized retrieval list 107. For example, the retrieval component 108 can receive a user record identifying a particular user of the social network services, send a request to the social network server 120 for all content 124 associated with the user, and receive and store the requested content 124.
In operation, users may authorize the content server 102 to receive the social network information 122 and/or the content 124 from the social network server 120 by providing the token 114, in certain embodiments. The token 114 may or may not expire after a preset period of time. In other embodiments, the user authorization may not be needed. With the token 114 or in cases where the user authorization is not needed, the content server 102 can request the social network information 122 from the social network server 120, which in turn transmits the requested social network information 122 to the content server 102.
The policy component 104 of the content server 102 then analyzes the received social network information 122 to generate the priority ratings 106 for the users associated with the received social network information 122. The priority ratings 106 individually represent a likelihood of existence of a user's published content or a likelihood of consumption of the user's published content by other users on the social network server 120. As used herein, the term “likelihood of consumption” generally refers to a likelihood that a user's published content is viewed, liked, re-posted, linked, and/or otherwise interacted with by other users. Based on the priority ratings 106, the policy component 104 can prioritize retrieval of the content 124 by identifying a subset of users whose published content 124 is more likely to exist (e.g., produced by the users after a previous retrieval) and/or be consumed than other users. In the illustrated embodiment, the policy component 104 generates the prioritized retrieval list 107 (e.g., a retrieval queue) based on the priority ratings 106. In other embodiments, the policy component 104 can also be based on other suitable criteria and/or utilize other suitable data structures. The retrieval component 108 may then retrieve content 124 based on the prioritized retrieval list 107 from the social network server 120.
The input module 160 is configured to receive the social network information 122 from the social network server 120 (
In other embodiments, the input module 160 can be configured to filter the social network information 122 for a particular type of content (e.g., news stories, photos, or videos), a particular type of interaction (e.g., status updates or comments on other users' status updates), a particular type of users (e.g., new users), or based on other suitable criteria. In further examples, the input module 160 can manipulate other parameters of the received social network information 122 by sorting, grouping, interpolating, and/or processing in other suitable manners. The input module 160 may include comparison, recursion, character parsing, or other suitable routines. In other embodiments, the input module 160 may be configured to receive data related to behaviors of the social network server 120, operator input 154 and/or other suitable input. In further embodiments, the input module 160 may be configured to perform the foregoing and/or other suitable operations during or after processing the social network information 122 by other modules of the policy component 104.
The calculation module 166 can be configured to calculate a priority rating 106 (
During calculations, certain parameters of the social network information 122 may be assigned numerical values. For instance, a new user may carry a numerical value that is higher than that of an existing user. A portion of updated content 124 may carry a numerical value that is higher than a portion of “stale” content 124 (i.e., one that has not been updated for a preset period of time). In further examples, the calculation module 166 may include routines for performing time averaging, window averaging, filtering, and/or other suitable operations. One example of calculating priority ratings 106 is described below in more detail with reference to
The analysis module 162 may be configured to analyze the social network information 122 and/or the calculated priority ratings 106 to determine a priority level of the individual users. For example, the analysis module 162 can be configured to assign a high priority level to users whose calculated priority ratings 106 are above a preset threshold, and assign a low priority level to other users whose calculated priority ratings 106 are below or equal to the preset threshold. In other examples, the analysis module 162 can be configured to assign three, four, or any other suitable number of priority levels to the users. In further examples, instead of assigning priority levels, the analysis module 162 can be configured to rank all users based on the corresponding priority ratings 106. In yet further examples, the analysis module 162 may prioritize the users in other suitable manners. The analysis module 162 can then supply the analysis results to the calculation module 166 and/or control module 164 for further processing.
The control module 164 may be configured to generate a prioritized retrieval list 107 (
In certain embodiments, the control module 164 can also generate the prioritized retrieval list 107 at least partially based on data related to the behaviors of the social network server 120 (
As discussed above, by prioritizing the retrieval of the content 124 from the social network server 120, several embodiments of the present technology can acquire relevant, popular, and/or useful content 124 in a timely fashion. For example, certain pieces of the content 124 that are more likely be consumed can be acquired and/or updated more frequently (e.g., once every 24 hours) than others. Also, several embodiments of the present technology can also adjust the retrieval of the content 124 based on behaviors of the social network server 120 to reduce or eliminate the risk of overloading the social network server 120 with content retrieval requests. For example, the content 124 may be retrieved when a load is below a predetermined threshold, at a certain time of day, or under other suitable conditions indicating a light load on the social network server 120. In other examples, the content 124 may be retrieved from parts of the social network server 120 with a light load by, for example, re-prioritizing the retrieval of the content based on a current condition of the social network server 120.
As shown in
The process 200 can then include receiving the social network information 122 at stage 204, for example, by the input module 160 of the policy component 104 (
The process 200 then includes generating one or more prioritized retrieval lists at stage 206. In one embodiment, the calculation module 166 (
In another embodiment, generating one or more prioritized retrieval lists can also include assigning a retrieval delay to each of the user records based on respective priority ratings. For example, if a user has a high priority rating associated with a high likelihood of consumption of published content by the user, the retrieval delay assigned to the user may be low. In another example, instead of assigning a retrieval delay, the retrieval delay may be calculated, for example, as an inversion, of the priority rating. In other examples, the retrieval delay may be derived in other suitable manners.
The process 200 can then include retrieving the content 124 from the social network server 120 at stage 208. In one embodiment, the retrieval component 108 (
In certain embodiments, retrieving the content 124 can also be at least partially based on data related to the behaviors of the social network server 120. For example, in one embodiment, retrieval from shared friends may be evenly distributed among tokens 114 to limit a number of retrieval requests in a certain time period. In another embodiment, retrieval of the content 124 may be generally aligned with an expiration time of the token 114. In yet another embodiment, retrieving the content 124 may be time sliced. As such, different items of the content 124 may be retrieved at different times to avoid or reduce a risk of exceeding item lists for a single request to the social network server. In another embodiment, retrieving the content 124 may be incremental to avoid or reduce a risk of duplicate requests. In further embodiments, retrieving the content 124 may be adjusted in other suitable manner based on the behaviors of the social network server 120.
The process 200 then includes a decision stage 210 to determine if the process continues. In one embodiment, the process 200 continues if additional social network information 122 is available. Thus, the process 200 reverts to receiving the social network information at stage 204. In other embodiments, the process 200 can continue based on other suitable conditions; otherwise, the process ends.
In the example illustrated in
In one example, a priority rating can be calculated for each of the users A-F periodically (e.g., every 24 hours) by multiplying a weighted sum of all queries of a user and the user's friends with a weighted sum of the number of items of published content by the user. Thus, according to the foregoing formula, the following table of priority ratings may be generated based on a weight factor of 1 for both parameters:
Based on the foregoing priority ratings, the users A-F may be sorted and certain users may be identified as high priority users if their priority ratings are above a preset threshold. For instance, in the example above, users D and E maybe identified as the high priority users if the threshold is 100. As such, the published content by D and E may be retrieved more frequently than that by the other users. As can be seen from this example, D and E are high priority users because (1) users D and E produce a large number of items of published content and/or (2) friends of D and E perform a large number of queries. As a result, the published content by users D and E are more likely be consumed by their friends in the social network 300 than the published content by the other users.
Depending on the desired configuration, the processor 504 may be of any type including but not limited to a microprocessor (μP), a microcontroller (μC), a digital signal processor (DSP), or any combination thereof. The processor 504 may include one more levels of caching, such as a level one cache 510 and a level two cache 512, a processor core 514, and registers 516. An example processor core 514 may include an arithmetic logic unit (ALU), a floating point unit (FPU), a digital signal processing core (DSP Core), or any combination thereof. An example memory controller 518 may also be used with processor 504, or in some implementations memory controller 518 may be an internal part of processor 504.
Depending on the desired configuration, the system memory 506 may be of any type including but not limited to volatile memory (such as RAM), non-volatile memory (such as ROM, flash memory, etc.) or any combination thereof. The system memory 506 may include an operating system 520, one or more applications 522, and program data 524. The application 522 may include, for example, the policy component 104 of the content server 102 (
The computing device 500 may have additional features or functionality, and additional interfaces to facilitate communications between basic configuration 502 and any other devices and interfaces. For example, a bus/interface controller 530 may be used to facilitate communications between the basic configuration 502 and one or more data storage devices 532 via a storage interface bus 534. The data storage devices 532 may be removable storage devices 536, non-removable storage devices 538, or a combination thereof. Examples of removable storage and non-removable storage devices include magnetic disk devices such as flexible disk drives and hard-disk drives (HDD), optical disk drives such as compact disk (CD) drives or digital versatile disk (DVD) drives, solid state drives (SSD), and tape drives to name a few. Example computer storage media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other data.
The system memory 506, removable storage devices 536 and non-removable storage devices 538 are examples of computer storage media. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which may be used to store the desired information and which may be accessed by computing device 500. Any such computer storage media may be part of computing device 500. The term “computer storage medium” excludes propagated signals and communication media.
The computing device 500 may also include an interface bus 540 for facilitating communication from various interface devices (e.g., output devices 542, peripheral interfaces 544, and communication devices 546) to the basic configuration 502 via bus/interface controller 530. Example output devices 542 include a graphics processing unit 548 and an audio processing unit 550, which may be configured to communicate to various external devices such as a display or speakers via one or more NV ports 552. Example peripheral interfaces 544 include a serial interface controller 554 or a parallel interface controller 556, which may be configured to communicate with external devices such as input devices (e.g., keyboard, mouse, pen, voice input device, touch input device, etc.) or other peripheral devices (e.g., printer, scanner, etc.) via one or more I/O ports 558. An example communication device 546 includes a network controller 560, which may be arranged to facilitate communications with one or more other computing devices 562 over a network communication link via one or more communication ports 564.
The network communication link may be one example of a communication media. Communication media may typically be embodied by computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and may include any information delivery media. A “modulated data signal” may be a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media may include wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), microwave, infrared (IR) and other wireless media. The term computer readable media as used herein may include both storage media and communication media.
The computing device 500 may be implemented as a portion of a small-form factor portable (or mobile) electronic device such as a cell phone, a personal data assistant (PDA), a personal media player device, a wireless web-watch device, a personal headset device, an application specific device, or a hybrid device that include any of the above functions. The computing device 500 may also be implemented as a personal computer including both laptop computer and non-laptop computer configurations.
Specific embodiments of the technology have been described above for purposes of illustration. However, various modifications may be made without deviating from the foregoing disclosure. In addition, many of the elements of one embodiment may be combined with other embodiments in addition to or in lieu of the elements of the other embodiments. Accordingly, the technology is not limited except as by the appended claims.
