# US 2015/0032740 A1 · Personal trends module > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2015/0032740 A1 - Document ID: US20150032740A1 - Status: Published application - Kind: A1 - Application number: 13/950,132 - Filed: 2013-07-24 - Published: 2015-01-29 - Earliest claimed: 2013-07-24 - Assignees: Yahoo! Inc. - Applicants: Yahoo! Inc. - Inventors: SUPREETH RAO; SUDHARSAN VASUDEVAN; GOPAL MOR; UTKARSH SHRIVASTAVA - Web page: https://patentgrep.com/patent/US20150032740A1 ## CPC - G06F 16/9535: Search customisation based on user profiles and personalisation - G06F 16/2455: Query execution - G06F 16/24575: {using context} - G06F 16/24578: {using ranking} - H04L 51/216: Handling conversation history, e.g. grouping of messages in sessions or threads - H04L 51/52: for supporting social networking services - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) ## Abstract A system and method for generating a personalized trends module includes steps of: for a given user, producing a social timeline by logging content posted on the given user's accounts on social media sites; analyzing the social timeline for recently posted content to derive an interim summary of first trending topics for the given user; receiving from a content personalization platform an in-stream feed of second trending topics based on the user's recent on-line activity including page views, queries, and clicks; augmenting the social timeline with the second trending topics from the in-stream feed to produce an interim list of third trending topics; ranking the third trending topics by source category using a frequency index; selecting the highest ranking third trending topics from each source category; and presenting a personalized trends module with positions allocated to the highest ranking third trending topics. ## Claims ### Claim 1 A computer-implemented method for generating personalized trending topics, comprising: using a processor device, performing steps of: for a given user, producing a social timeline by logging content posted on the given user's accounts on social media sites; analyzing the social timeline for recently posted content to derive an interim summary of first trending topics for the given user; receiving an in-stream feed of second trending topics based on the user's recent on-line activity including page views, queries, and clicks; augmenting the social timeline with the second trending topics from the in-stream feed to produce an interim list of third trending topics; ranking the third trending topics by source category using a frequency index; selecting a subset of highest ranked third trending topics from each source category; and presenting a personalized trends module comprising positions allocated to the subset of the highest ranked third trending topics. ### Claim 2 (depends on 1) The computer-implemented method of claim 1 further comprising: ranking the source categories by the frequency index; wherein the source categories comprise social media and on-line activity. ### Claim 3 (depends on 2) The computer-implemented method of claim 2 wherein selecting the subset of the highest ranked third trending topics comprises: weighting the selection proportionately to the ranking of the source categories, such that the source category with more occurrences in the timeline is allocated more positions in the personalized topics module than a source category with fewer occurrences in the timeline. ### Claim 4 (depends on 3) The computer-implemented method of claim 3 further comprising: allocating a position for at least one global trending topic from a publisher's site to the personalized trends module; retrieving the at least one global trending topic; and adding the at least one global trending topic before presenting the personalized trends module. ### Claim 5 (depends on 4) The computer-implemented method of claim 4 wherein presenting the personalized trends module comprises presenting the topics such that the first trending topics, the second trending topics, the third trending topics, and the at least one global trending topic are distinguishable by assigning a different appearance to the topics based on source category. ### Claim 6 (depends on 4) The computer-implemented method of claim 4 further comprising: allocating a position for a sponsored trending topic in the personalized trends module; and adding the sponsored trending topic to the personalized trends module. ### Claim 7 (depends on 4) The computer-implemented method of claim 4 further comprising: adding an advertisement to the personalized trends module. ### Claim 8 (depends on 4) The computer-implemented method of claim 4 further comprising: adding an identifier of the given user to the personalized trends module. ### Claim 9 (depends on 4) The computer-implemented method of claim 4 further comprising: performing the analyzing, receiving, augmenting, ranking, selecting, and presenting steps at periodic intervals. ### Claim 10 (depends on 4) The computer-implemented method of claim 4 further comprising: performing the analyzing, receiving, augmenting, ranking, selecting, and presenting steps at random intervals, based on the user's on-line activity. ### Claim 11 (depends on 9) The computer-implemented method of claim 9 wherein performing the steps at periodic intervals further comprises performing the steps of retrieving and adding the at least one global trending topic at different periodic intervals. ### Claim 12 An information processing system for generating personalized trending topics comprises: a processor device; and a memory operably coupled with the processor device, said memory comprising computer-executable instructions causing a computer to perform steps of: for a given user, producing a social timeline by logging content posted on the given user's accounts on social media sites; analyzing the social timeline for recently posted content to derive an interim summary of first trending topics for the user; receiving an in-stream feed of second trending topics based on the user's recent on-line activity such as page views, queries, and clicks; augmenting the social timeline with the second trending topics from the in-stream feed to produce an interim list of third trending topics; ranking the third trending topics by source category using a frequency index; selecting a subset of highest ranked third trending topics from each source category; and presenting a personalized trends module comprising positions allocated to the subset of the highest ranked third trending topics. ### Claim 13 (depends on 12) The information processing system of claim 12 wherein the computer-executable instructions further comprise instructions for: ranking the source categories by the frequency index; wherein the source categories comprise social media and on-line activity; and wherein selecting the subset of the highest ranked third trending topics comprises weighting the selection proportionately to the ranking of the source categories, such that the source category with more occurrences in the timeline is allocated more positions in the personalized topics module than a source category with fewer occurrences in the timeline. ### Claim 14 (depends on 13) The information processing system of claim 13 wherein the computer-executable instructions further comprise instructions for: allocating a position for at least one global trending topic from a publisher's site to the personalized trends module; retrieving the at least one global trending topic; and adding the at least one global trending topic before presenting the personalized trends module. ### Claim 15 (depends on 13) The information processing system of claim 13 wherein the computer-executable instructions further comprise instructions for: presenting the topics in the personalized trends module such that the first trending topics, the second trending topics, the third trending topics, and the at least one global trending topic are distinguishable by assigning a different appearance to the topics based on source category. ### Claim 16 (depends on 13) The information processing system of claim 13 wherein the computer-executable instructions further comprise instructions for: allocating a position for a sponsored trending topic in the personalized trends module; and adding the sponsored trending topic to the personalized trends module. ### Claim 17 (depends on 13) The information processing system of claim 13 wherein the computer-executable instructions further comprise instructions for: adding an advertisement to the personalized trends module. ### Claim 18 (depends on 13) The information processing system of claim 13 wherein the computer-executable instructions further comprise instructions for: adding an identifier of the given user to the personalized trends module. ### Claim 19 A computer program product comprising a non-transitory computer-readable storage medium with computer-executable instructions stored thereon, said computer-executable instructions, when executed, causing a computer to perform steps of: for a given user, producing a social timeline by logging content posted on the given user's accounts on social media sites; analyzing the social timeline for recently posted content to derive an interim summary of first trending topics for the user; receiving an in-stream feed of second trending topics based on the user's recent on-line activity such as page views, queries, and clicks; augmenting the social timeline with the second trending topics from the in-stream feed to produce an interim list of third trending topics; ranking the third trending topics by source category using a frequency index; selecting a subset of highest ranked third trending topics from each source category; and presenting a personalized trends module comprising positions allocated to the subset of the highest ranked third trending topics. ### Claim 20 (depends on 19) The computer program product of claim 19 wherein the computer-executable instructions further cause a computer to perform: ranking the source categories by the frequency index; wherein the source categories comprise social media and on-line activity; and wherein selecting the subset of the highest ranked third trending topics comprises weighting the selection proportionately to the ranking of the source categories, such that the source category with more occurrences in the timeline is allocated more positions in the personalized topics module than a source category with fewer occurrences in the timeline.