# US 12,001,971 B2 · Method and system for exploring a personal interest space > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,001,971 B2 - Document ID: US12001971B2 - Status: Granted - Kind: B2 - Application number: 17/966,288 - Filed: 2022-10-14 - Published: 2023-02-02 - Granted: 2024-06-04 - Earliest claimed: 2022-10-14 - Assignees: Particle Media, Inc. - Applicants: Particle Media, Inc. - Inventors: Zhaohui Zheng - Web page: https://patentgrep.com/patent/US12001971B2 ## CPC - G06N 5/045: Explanation of inference; Explainable artificial intelligence [XAI]; Interpretable artificial intelligence - G06F 16/335: Filtering based on additional data, e.g. user or group profiles (filtering in web context G06F16/9535, G06F16/9536) - G06F 16/9027: {Trees} - G06F 16/9535: Search customisation based on user profiles and personalisation - G06N 5/01: Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound - G06N 20/00: Machine learning - G06N 20/20: Ensemble learning - G06Q 30/02: Marketing; Price estimation or determination; Fundraising - G06Q 30/0224: {based on user history} - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR ## Abstract The present teaching relates to exploring a personal interest space based on a decision tree. In one example, information related to a personal interest space associated with a user is obtained. The personal interest space includes at least one channel of content that the user is interested in. A decision tree created based on information related to a plurality of users with respect to a plurality of channels of content is obtained. Each node of the decision tree is associated with at least one of the plurality of channels of content. A first node of the decision tree is identified based on the information related to the personal interest space associated with the user. A question for the user in connection with the first node of the decision tree is determined. An answer to the question is received from the user. A second node of the decision tree is identified based on the answer. The personal interest space associated with the user is updated based on the at least one channel of content associated with the second node of the decision tree. ## Claims ### Claim 1 A method, implemented on a machine having at least one processor, storage, and a communication platform connected to a network for exploring interests of a user, the method comprising: obtaining a user profile of the user; selecting, based on the user profile, a user subset based decision tree that is trained based on training data associated with one or more other users similar to the user; determining, based on a user personal interest space, one or more channels subscribed by the user; selecting, based on the one or more subscribed channels, a channel subset based decision tree that is trained based on training data associated with channel features related to the one or more subscribed channels; retrieving a generic decision tree that is trained based on training data associated with a general population; creating a personal decision forest including the user subset based decision tree, the channel subset based decision tree, and the generic decision tree; updating, by an interest engine, the user personal interest space based on an answer to a question, wherein the question is selected by the interest engine based on the personal decision forest; and generating, by the interest engine to the user, an online content stream based on the updated user personal interest space. ### Claim 2 (depends on 1) The method of claim 1, further comprising: determining, based on the one or more subscribed channels, a current channel vector; and identifying, based on the current channel vector, a node in the personal decision forest. ### Claim 3 (depends on 2) The method of claim 2, further comprising: determining whether there is any contradiction between the identified node and information of the user indicated by the user profile. ### Claim 4 (depends on 3) The method of claim 3, further comprising: if there is no contradiction, selecting the question based on the identified node and the information of the user. ### Claim 5 (depends on 3) The method of claim 3, further comprising: if there is contradiction, identifying a different node in the personal decision forest; and selecting the question based on the different node and the information of the user. ### Claim 6 (depends on 1) The method of claim 1, further comprising: receiving, from the user, the answer to the question; and updating the personal interest space based on the answer. ### Claim 7 A non-transitory, computer-readable medium having information recorded thereon for exploring interests of a user, when read by at least one processor, effectuate operations comprising: obtaining a user profile of the user; selecting, based on the user profile, a user subset based decision tree that is trained based on training data associated with one or more other users similar to the user; determining, based on a user personal interest space, one or more channels subscribed by the user; selecting, based on the one or more subscribed channels, a channel subset based decision tree that is trained based on training data associated with channel features related to the one or more subscribed channels; retrieving a generic decision tree that is trained based on training data associated with a general population; creating a personal decision forest including the user subset based decision tree, the channel subset based decision tree, and the generic decision tree; updating the user personal interest space based on an answer to a question, wherein the question is selected by an interest engine based on the personal decision forest; and generating, to the user, an online content stream based on the updated user personal interest space. ### Claim 8 (depends on 7) The medium of claim 7, wherein the operations further comprise: determining, based on the one or more subscribed channels, a current channel vector; and identifying, based on the current channel vector, a node in the personal decision forest. ### Claim 9 (depends on 8) The medium of claim 8, wherein the operations further comprise: determining whether there is any contradiction between the identified node and information of the user indicated by the user profile. ### Claim 10 (depends on 9) The medium of claim 9, wherein the operations further comprise: if there is no contradiction, selecting the question based on the identified node and the information of the user. ### Claim 11 (depends on 9) The medium of claim 9, wherein the operations further comprise: if there is contradiction, identifying a different node in the personal decision forest; and selecting the question based on the different node and the information of the user. ### Claim 12 (depends on 7) The medium of claim 7, wherein the operations further comprise: receiving, from the user, the answer to the question; and updating the personal interest space based on the answer. ### Claim 13 A system for exploring interests of a user, the system comprising: memory storing computer program instructions; and one or more processors that, in response to executing the computer program instructions, effectuate operations comprising: obtaining a user profile of the user; selecting, based on the user profile, a user subset based decision tree that is trained based on training data associated with one or more other users similar to the user; determining, based on a user personal interest space, one or more channels subscribed by the user; selecting, based on the one or more subscribed channels, a channel subset based decision tree that is trained based on training data associated with channel features related to the one or more subscribed channels; retrieving a generic decision tree that is trained based on training data associated with a general population; creating a personal decision forest including the user subset based decision tree, the channel subset based decision tree, and the generic decision tree; updating the user personal interest space based on an answer to a question, wherein the question is selected by an interest engine based on the personal decision forest; and generating, to the user, an online content stream based on the updated user personal interest space. ### Claim 14 (depends on 13) The system of claim 13, wherein the operations further comprise: determining, based on the one or more subscribed channels, a current channel vector; and identifying, based on the current channel vector, a node in the personal decision forest. ### Claim 15 (depends on 14) The system of claim 14, wherein the operations further comprise: determining whether there is any contradiction between the identified node and information of the user indicated by the user profile. ### Claim 16 (depends on 15) The system of claim 15, wherein the operations further comprise: if there is no contradiction, selecting the question based on the identified node and the information of the user. ### Claim 17 (depends on 15) The system of claim 15, wherein the operations further comprise: if there is contradiction, identifying a different node in the personal decision forest; and selecting the question based on the different node and the information of the user.