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Simple time-aware and social-aware user similarity for a KNN-based recommender system

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

2 Scopus citations

Abstract

In this paper we report the results of the experiment carried out by our institutions for participating in the track 1 of the the 2011 CAMRa challenge workshop. We ran some variations of a traditional user-based neighborhood recommender system based on two simple ideas: (1) Force the inclusion of household members into the neighborhood of the user and (2) increase the similarity of users that use the system if they use the system at similar time slots. The approaches are evaluated using the MAP, P@5, P@10 and AUC metrics. Results show that a small improvement is achieved on of the chosen metrics when comparing the social and time strategies to a traditional KNN approach.

Original languageEnglish
Title of host publication5th ACM Conference on Recommender Systems - Proceedings of the RecSys'2011 ACM
Subtitle of host publicationChallenge on Context-Aware Movie Recommendation, CAMRa 2011
Pages36-38
Number of pages3
DOIs
StatePublished - 2011
Externally publishedYes
Event5th ACM Conference on Recommender Systems, RecSys'2011: 2nd Challenge on Context-Aware Movie Recommendation, CAMRa 2011 - Chicago, IL, United States
Duration: 23 Oct 201127 Oct 2011

Publication series

NameACM International Conference Proceeding Series

Conference

Conference5th ACM Conference on Recommender Systems, RecSys'2011: 2nd Challenge on Context-Aware Movie Recommendation, CAMRa 2011
Country/TerritoryUnited States
CityChicago, IL
Period23/10/1127/10/11

Keywords

  • Performance
  • Recommender systems

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