Rank-GeoFM: a ranking based geographical factorization method for point of interest recommendation

Xutao Li, Gao Cong, Xiao-Li Li, Tuan-Anh Nguyen Pham, Shonali Krishnaswamy

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

205 Citations (Scopus)

Abstract

With the rapid growth of location-based social networks, Point of Interest (POI) recommendation has become an important research problem. However, the scarcity of the check-in data, a type of implicit feedback data, poses a severe challenge for existing POI recommendation methods. Moreover, different types of context information about POIs are available and how to leverage them becomes another challenge. In this paper, we propose a ranking based geographical factorization method, called Rank-GeoFM, for POI recommendation, which addresses the two challenges. In the proposed model, we consider that the check-in frequency characterizes users' visiting preference and learn the factorization by ranking the POIs correctly. In our model, POIs both with and without check-ins will contribute to learning the ranking and thus the data sparsity problem can be alleviated. In addition, our model can easily incorporate different types of context information, such as the geographical influence and temporal influence. We propose a stochastic gradient descent based algorithm to learn the factorization. Experiments on publicly available datasets under both user-POI setting and user-time-POI setting have been conducted to test the effectiveness of the proposed method. Experimental results under both settings show that the proposed method outperforms the state-of-the-art methods significantly in terms of recommendation accuracy.
Original languageEnglish
Title of host publicationSIGIR 2015 - Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval
EditorsAlistair Moffat, Mounia Lalmas, Berthier Ribeiro-Neto
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages433-442
Number of pages10
ISBN (Print)9781450336215
DOIs
Publication statusPublished - 2015
Externally publishedYes
EventACM International Conference on Research and Development in Information Retrieval 2015 - Santiago, Chile
Duration: 9 Aug 201513 Aug 2015
Conference number: 38th
https://dl.acm.org/doi/proceedings/10.1145/2766462

Conference

ConferenceACM International Conference on Research and Development in Information Retrieval 2015
Abbreviated titleSIGIR 2015
CountryChile
CitySantiago
Period9/08/1513/08/15
OtherProceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2015)
Internet address

Keywords

  • Collaborative Filtering
  • Factorization Model
  • Ranking

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