On building entity recommender systems using user click log and freebase knowledge

Xiao Yu, Hao Ma, Bo June Hsu, Jiawei Han

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Due to their commercial value, search engines and recommender systems have become two popular research topics in both industry and academia over the past decade. Although these two fields have been actively and extensively studied separately, researchers are beginning to realize the importance of the scenarios at their intersection: providing an integrated search and information discovery user experience. In this paper, we study a novel application, i.e., personalized entity recommendation for search engine users, by utilizing user click log and the knowledge extracted from Freebase. To better bridge the gap between search engines and recommender systems, we first discuss important heuristics and features of the datasets. We then propose a generic, robust, and time-aware personalized recommendation framework to utilize these heuristics and features at different granularity levels. Using movie recommendation as a case study, with user click log dataset collected from a widely used commercial search engine, we demonstrate the effectiveness of our proposed framework over other popular and state-of-the-art recommendation techniques.

Original languageEnglish (US)
Title of host publicationWSDM 2014 - Proceedings of the 7th ACM International Conference on Web Search and Data Mining
PublisherAssociation for Computing Machinery
Pages263-272
Number of pages10
ISBN (Print)9781450323512
DOIs
StatePublished - 2014
Event7th ACM International Conference on Web Search and Data Mining, WSDM 2014 - New York, NY, United States
Duration: Feb 24 2014Feb 28 2014

Publication series

NameWSDM 2014 - Proceedings of the 7th ACM International Conference on Web Search and Data Mining

Other

Other7th ACM International Conference on Web Search and Data Mining, WSDM 2014
CountryUnited States
CityNew York, NY
Period2/24/142/28/14

Keywords

  • entity graph
  • entity recommendation
  • personalization
  • search click log
  • user behavior analysis

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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