App recommendation: A contest between satisfaction and temptation

Peifeng Yin, Ping Luo, Wang-chien Lee, Min Wang

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

72 Scopus citations

Abstract

Due to the huge and still rapidly growing number of mobile applications (apps), it becomes necessary to provide users an app recommendation service. Different from conventional item recommendation where the user interest is the primary factor, app recommendation also needs to consider factors that invoke a user to replace an old app (if she already has one) with a new app. In this work we propose an Actual- Tempting model that captures such factors in the decision process of mobile app adoption. The model assumes that each owned app has an actual satisfactory value and a new app under consideration has a tempting value. The former stands for the real satisfactory value the owned app brings to the user while the latter represents the estimated value the new app may seemingly have. We argue that the process of app adoption therefore is a contest between the owned apps' actual values and the candidate app's tempting value. Via the extensive experiments we show that the AT model performs significantly better than the conventional recommendation techniques such as collaborative filtering and content-based recommendation. Furthermore, the best recommendation performance is achieved when the AT model is combined with them.

Original languageEnglish (US)
Title of host publicationWSDM 2013 - Proceedings of the 6th ACM International Conference on Web Search and Data Mining
Pages395-404
Number of pages10
DOIs
StatePublished - Feb 28 2013
Event6th ACM International Conference on Web Search and Data Mining, WSDM 2013 - Rome, Italy
Duration: Feb 4 2013Feb 8 2013

Publication series

NameWSDM 2013 - Proceedings of the 6th ACM International Conference on Web Search and Data Mining

Other

Other6th ACM International Conference on Web Search and Data Mining, WSDM 2013
CountryItaly
CityRome
Period2/4/132/8/13

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications

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