Computer implemented methods and apparatus for implementing a topical-based highlights filter
US-9367626-B2 · Jun 14, 2016 · US
US9984126B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9984126-B2 |
| Application number | US-201414445950-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jul 29, 2014 |
| Priority date | Jul 23, 2012 |
| Publication date | May 29, 2018 |
| Grant date | May 29, 2018 |
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Disclosed are techniques for identifying data items to display in a feed of an enterprise social networking system. A first subset of data items is identified as associated with an inner circle of data sources with which a user interacts at or exceeding a designated frequency, a second subset of data items is identified as associated with an interest graph associated with the user, and a third subset of data items is identified as associated with a group or an organization. A highlights feed can be displayed with different channels, where a first channel is defined by the first subset of data items, a second channel is defined by the second subset of data items, and a third channel is defined by the third subset of data items.
Opening claim text (preview).
What is claimed is: 1. A system for identifying relevant feed items to display in a feed of an enterprise social networking system, the system comprising: a database system implemented using a server system comprising one or more processors, the database system configured to cause: identifying from a plurality of data sources associated with an enterprise social networking system: a first subset of data items as having a first characteristic satisfying a first relevance parameter indicating relevance to a user of the enterprise social networking system, the first relevance parameter identifying an inner circle of data sources as a subset of the data sources with which the user interacts at or exceeding a user-designated frequency, a second subset of data items as having a second characteristic satisfying a second relevance parameter indicating relevance to the user, the second relevance parameter defined by an interest graph associated with the user, the interest graph maintained as a data structure using one or more data objects in a database to identify topics, feed items and keywords designated as being of interest to the user, and a third subset of data items as having a third characteristic satisfying a third relevance parameter indicating relevance to the user, the third relevance parameter identifying a group or an organization with which the user is associated; displaying a highlights feed on a display device, the displayed highlights feed comprising a plurality of channels, each channel graphically identified as associated with a respective relevance parameter, the channels comprising a first channel defined by the first subset of data items, a second channel defined by the second subset of data items, and a third channel defined by the third subset of data items; updating the interest graph associated with the user based on user input corresponding to user activity with respect to one or more of the plurality of data sources, the updating of the interest graph comprising updating the one or more data objects in the database; updating the second characteristic based on the updated interest graph; updating the highlights feed according to the updated characteristic; identifying a further data source based on an analysis of a combination of the updated interest graph with one or more of a social graph associated with the user or a sentiment graph associated with a user; generating a recommendation of the further data source as being relevant to the user; and sending the recommendation to a computing device associated with the user. 2. The system of claim 1 , wherein the first characteristic is a score. 3. The system of claim 1 , wherein identifying the first, second and third subsets of data items comprises: applying a filter having the first, second and third relevance parameters. 4. The system of claim 1 , wherein the inner circle of data sources comprises: a database record with which the user has a working relationship. 5. The system of claim 1 , wherein the second characteristic is content of the second subset of data items being identified by the interest graph. 6. The system of claim 1 , the database system further configured to cause: updating the highlights feed in response to a user input specifying that at least one of the data items in the first, second or third subsets is not relevant to the user. 7. The system of claim 1 , the database system further configured to cause: updating one or more weights associated with one or more of the relevance parameters using one or more of: a machine learning process, a heuristic process, and a regression process. 8. The system of claim 1 , wherein the interest graph associated with the user identifies subject matter with which the user interacts at or exceeding a designated frequency. 9. The system of claim 1 , wherein relevance of a data item in the third subset to a group or an organization is based at least in part on a level of importance indicated by one or more other users regarding the data item. 10. The system of claim 9 , wherein the relevance of the data item in the third subset to the group or the organization is further based on sharing of one or more attributes by the user with the one or more other users. 11. A computer-implemented method for identifying relevant feed items to display in a feed of an enterprise social networking system, the method comprising: identifying, using a database system, from a plurality of data sources associated with an enterprise social networking system: a first subset of data items as having a first characteristic satisfying a first relevance parameter indicating relevance to a user of the enterprise social networking system, the first relevance parameter identifying an inner circle of data sources as a subset of the data sources with which the user interacts at or exceeding a user-designated frequency, a second subset of data items as having a second characteristic satisfying a second relevance parameter indicating relevance to the user, the second relevance parameter defined by an interest graph associated with the user, the interest graph maintained as a data structure using one or more data objects in a database to identify topics, feed items and keywords designated as being of interest to the user, and a third subset of data items as having a third characteristic satisfying a third relevance parameter indicating relevance to the user, the third relevance parameter identifying a group or an organization with which the user is associated; causing display of a highlights feed on a display device, the displayed highlights feed comprising a plurality of channels, each channel graphically identified as associated with a respective relevance parameter, the channels comprising a first channel defined by the first subset of data items, a second channel defined by the second subset of data items, and a third channel defined by the third subset of data items; causing updating of the interest graph associated with the user based on user input corresponding to user activity with respect to one or more of the plurality of data sources, the updating of the interest graph comprising updating the one or more data objects in the database; causing updating of the second characteristic based on the updated interest graph; causing updating of the highlights feed according to the updated characteristic; identifying a further data source based on an analysis of a combination of the updated interest graph with one or more of a social graph associated with the user or a sentiment graph associated with a user; causing generating of a recommendation of the further data source as being relevant to the user; and causing sending of the recommendation to a computing device associated with the user. 12. The method of claim 11 , wherein identifying the first, second and third subsets of data items comprises: applying a filter having the first, second and third relevance parameters. 13. The method of claim 11 , wherein the inner circle of data sources comprises: a database record with which the user has a working relationship. 14. The method of claim 11 , further comprising: updating one or more weights associated with one or more of the relevance parameters using one or more of: a machine learning process, a heuristic process, and a regression process. 15. A computer program product comprising computer-readable program code to be executed by one or more processors when retrieved from a non-transitory computer-readable medium for identifying relevant feed items to display in a feed of an enterprise social netwo
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