Leveraging user reviews to improve accuracy for mobile app retrieval

Dae Hoon Park, Mengwen Liu, Chengxiang Zhai, Haohong Wang

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

Abstract

Smartphones and tablets with their apps pervaded our everyday life, leading to a new demand for search tools to help users find the right apps to satisfy their immediate needs. While there are a few commercial mobile app search engines available, the new task of mobile app retrieval has not yet been rigorously studied. Indeed, there does not yet exist a test collection for quantitatively evaluating this new retrieval task. In this paper, we first study the effectiveness of the state-of-the-art retrieval models for the app retrieval task using a new app retrieval test data we created. We then propose and study a novel approach that generates a new representation for each app. Our key idea is to leverage user reviews to find out important features of apps and bridge vocabulary gap between app developers and users. Specifically, we jointly model app descriptions and user reviews using topic model in order to generate app representations while excluding noise in reviews. Experiment results indicate that the proposed approach is effective and outperforms the state-of-the-art retrieval models for app retrieval.

Original languageEnglish (US)
Title of host publicationSIGIR 2015 - Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval
PublisherAssociation for Computing Machinery, Inc
Pages533-542
Number of pages10
ISBN (Electronic)9781450336215
DOIs
StatePublished - Aug 9 2015
Event38th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2015 - Santiago, Chile
Duration: Aug 9 2015Aug 13 2015

Publication series

NameSIGIR 2015 - Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval

Other

Other38th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2015
CountryChile
CitySantiago
Period8/9/158/13/15

ASJC Scopus subject areas

  • Information Systems
  • Software

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