Crafting a time-aware point-of-interest recommendation via pairwise interaction tensor factorization

Xinqiang Zhao, Xin Li*, Lejian Liao, Dandan Song, Kwok Wai CHEUNG

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

7 Citations (Scopus)


Location-based social networks have been increasingly used to experience users new possibilities, including personalized point-ofinterest (POI) recommendation services which leverages on the overlapping of user trajectories to recommend POI collaboratively. POI recommendation is challenging as it does not just suffers from the problems known for collaborative filtering such as data sparsity and cold-start, but to a much greater extent. Most of the related works apply the conventional recommendation approaches to POI recommendation while overlooking the personalized time-variant human behavioral tendency. In this paper, we put forward a tensor factorization-based ranking methodology to recommend users their interested locations by considering their timevarying behavioral trends. We also propose to categorize the locations to address data sparsity and cold-start issues, and accordingly new locations the user have not been visited can thus be bubbled up during ranking the location candidates. The tensor factorization is carefully studied to prune the irrelevant factors to the ranking results to achieve efficient POI recommendation. The experimental results validate the effectiveness of our proposed mechanism which outperforms the state-of-the-art approaches by over 8% for precision.

Original languageEnglish
Title of host publicationKnowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings
EditorsZili Zhang, Songmao Zhang, Zili Zhang, Martin Wirsing, Martin Wirsing, Martin Wirsing, Zili Zhang, Songmao Zhang, Songmao Zhang
PublisherSpringer Verlag
Number of pages13
ISBN (Print)9783319251585, 9783319251585, 9783319251585
Publication statusPublished - 2015
Event8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015 - Chongqing, China
Duration: 28 Oct 201530 Oct 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • Markov chain
  • POI recommendation
  • Tensor


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