Recommendations meet web browsing: Enhancing collaborative filtering using internet browsing logs

Royi Ronen, Elad Yom-Tov, Gal Lavee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

Collaborative filtering (CF) recommendation systems are one of the most popular and successful methods for recommending products to people. CF systems work by finding similarities between different people according to their past purchases, and using these similarities to suggest possible items of interest. In this work we show that CF systems can be enhanced using Internet browsing data and search engine query logs, both of which represent a rich profile of individuals' interests.

Original languageEnglish
Title of host publication2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1230-1238
Number of pages9
ISBN (Electronic)9781509020195
DOIs
StatePublished - 22 Jun 2016
Externally publishedYes
Event32nd IEEE International Conference on Data Engineering, ICDE 2016 - Helsinki, Finland
Duration: 16 May 201620 May 2016

Publication series

Name2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016

Conference

Conference32nd IEEE International Conference on Data Engineering, ICDE 2016
Country/TerritoryFinland
CityHelsinki
Period16/05/1620/05/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

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