Vector representation based model considering randomness of user mobility for predicting potential users

Shaowen Peng, Xianzhong Xie, Tsunenori Mine, Chang Su

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

Abstract

With increasing popularity of location-based social networks, POI recommendation has received much attention recently. Unlike most of the current studies which provide recommendations from perspective of users, in this paper, we focus on the perspective of Point-of-Interest (POI) for predicting potential users for a given POI. We propose a novel vector representation model for the prediction. Many current matrix factorization-based methods only pay attention to combining new information and basic matrix factorization, while in our model, we improve the matrix factorization model itself by replacing dot product with cosine similarity. We also address the problem of randomness of user’s check-in behavior by applying deep neural network to modeling the relationships between the user’s current check-in and context information of current check-in. Extensive experiments conducted on two real-world datasets demonstrate the superior performance of our proposed model and the effectiveness of the factors incorporated in our model.

Original languageEnglish
Title of host publicationPRIMA 2018
Subtitle of host publicationPrinciples and Practice of Multi-Agent Systems - 21st International Conference, 2018, Proceedings
EditorsNir Oren, Yuko Sakurai, Itsuki Noda, Tran Cao Son, Tim Miller, Bastin Tony Savarimuthu
PublisherSpringer Verlag
Pages70-85
Number of pages16
ISBN (Print)9783030030971
DOIs
Publication statusPublished - Jan 1 2018
Event21st International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2018 - Tokyo, Japan
Duration: Oct 29 2018Nov 2 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11224 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other21st International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2018
CountryJapan
CityTokyo
Period10/29/1811/2/18

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Peng, S., Xie, X., Mine, T., & Su, C. (2018). Vector representation based model considering randomness of user mobility for predicting potential users. In N. Oren, Y. Sakurai, I. Noda, T. Cao Son, T. Miller, & B. T. Savarimuthu (Eds.), PRIMA 2018: Principles and Practice of Multi-Agent Systems - 21st International Conference, 2018, Proceedings (pp. 70-85). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11224 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-030-03098-8_5