US 11,720,572 B2
Method and system for content recommendation
Yangyang Liu, Hangzhou (CN)
Assigned to ADVANCED NEW TECHNOLOGIES CO., LTD., George Town (KY)
Filed by ADVANCED NEW TECHNOLOGIES CO., LTD., Grand Cayman (KY)
Filed on Jun. 24, 2020, as Appl. No. 16/911,000.
Application 16/911,000 is a continuation in part of application No. PCT/CN2018/123283, filed on Dec. 25, 2018.
Claims priority of application No. 201810015028.0 (CN), filed on Jan. 8, 2018.
Prior Publication US 2020/0320086 A1, Oct. 8, 2020
Int. Cl. G06F 16/2457 (2019.01); G06N 20/00 (2019.01); G06F 16/28 (2019.01); G06F 16/2452 (2019.01); G06F 40/40 (2020.01)
CPC G06F 16/24573 (2019.01) [G06F 16/24522 (2019.01); G06F 16/282 (2019.01); G06F 40/40 (2020.01); G06N 20/00 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A computer-executable method, comprising:
selecting a content piece from a content library;
extracting, by a computer using a natural language processing (NLP) technique, one or more keywords from the content piece;
determining a domain associated with the content piece based on the extracted one or more keywords;
obtaining hierarchical domain knowledge of the determined domain, wherein the obtained hierarchical domain knowledge is based on a tree structure comprising a root node corresponding to a domain name, a number of leaf nodes corresponding to feature words each having a respective defined meaning within the determined domain, and one or more branch nodes corresponding to one or more categories within the determined domain;
obtaining one or more domain-knowledge graphs, a domain-knowledge graph of the one or more domain-knowledge graphs including an entity name and a number of attribute words associated with the entity name, the entity name and an attribute word indicating a feature combination word that is specific to the domain;
generating a feature tag for the content piece based on the extracted one or more keywords and the obtained hierarchical domain knowledge;
generating an attribute tag for a user based on historical data associated with the user; and
recommending one or more content pieces from the content library to the user based on feature tags associated with the one or more content pieces and the attribute tag for the user,
wherein the generating the feature tag includes:
comparing the extracted one or more keywords with one or more feature combination words defined by the one or more domain-knowledge graphs;
identifying an extracted keyword that matches a feature combination word of the one or more feature combination words; and
adding the identified extracted keyword to the feature tag.