Context-aware application prediction and recommendation in mobile devices

Satoshi Kurihara, Koichi Moriyama, Masayuki Numao

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

5 Citations (Scopus)

Abstract

In recent years, highly-functional mobile devices such as smart phones and car navigation systems are widely used. These are important for our daily life because we use their applications anywhere and anytime. With the variety of applications available on these devices, however, it becomes more difficult to choose an appropriate application. Therefore we need a mechanism that recommends us suitable applications, which should depend on a user's context because he/she uses his/her devices differently in every context. This paper shows that it follows a power law what applications a user executes in daily life, and proposes a novel approach to find context-aware applications in the mobile devices. This approach is based on the term frequency - inverse document frequency (TF-IDF), which is used for extracting important keywords in a document. Moreover, we propose an application recommendation mechanism using this approach. Experimental results show that this recommendation mechanism is more effective than the mechanism using Naive Bayes.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2013
Pages494-500
Number of pages7
Volume1
DOIs
Publication statusPublished - 2013 Dec 1
Externally publishedYes
Event2013 12th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2013 - Atlanta, GA, United States
Duration: 2013 Nov 172013 Nov 20

Other

Other2013 12th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2013
CountryUnited States
CityAtlanta, GA
Period13/11/1713/11/20

Fingerprint

Mobile devices
Navigation systems
Railroad cars

Keywords

  • Context-aware
  • IF-IDF
  • Navigation
  • Recommendation
  • Scale-free

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Kurihara, S., Moriyama, K., & Numao, M. (2013). Context-aware application prediction and recommendation in mobile devices. In Proceedings - 2013 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2013 (Vol. 1, pp. 494-500). [6690056] https://doi.org/10.1109/WI-IAT.2013.69

Context-aware application prediction and recommendation in mobile devices. / Kurihara, Satoshi; Moriyama, Koichi; Numao, Masayuki.

Proceedings - 2013 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2013. Vol. 1 2013. p. 494-500 6690056.

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

Kurihara, S, Moriyama, K & Numao, M 2013, Context-aware application prediction and recommendation in mobile devices. in Proceedings - 2013 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2013. vol. 1, 6690056, pp. 494-500, 2013 12th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2013, Atlanta, GA, United States, 13/11/17. https://doi.org/10.1109/WI-IAT.2013.69
Kurihara S, Moriyama K, Numao M. Context-aware application prediction and recommendation in mobile devices. In Proceedings - 2013 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2013. Vol. 1. 2013. p. 494-500. 6690056 https://doi.org/10.1109/WI-IAT.2013.69
Kurihara, Satoshi ; Moriyama, Koichi ; Numao, Masayuki. / Context-aware application prediction and recommendation in mobile devices. Proceedings - 2013 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2013. Vol. 1 2013. pp. 494-500
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