Demand prediction based on social context for mobile content services

Hiroyuki Kubo, Ryoichi Shinkuma, Tatsuro Takahashi, Hiroyuki Kasai, Kazuhiro Yamaguchi, Roy Yates

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

8 Citations (Scopus)

Abstract

The recent enhancement of mobile devices and wireless networks has enabled content services in mobile environments. Demand prediction is a traditional but powerful technique used for content services. However, it is hard to predict local demand in mobile environments because it depends not only on just user preference and the popularity of common content but also on other factors; users request content related to their locations; moreover, they are interested in the content uploaded by their friends who visited the location before them. Thus, we need to consider the context with multiple factors affecting the demand. In addition, we also need to consider the sequence of contexts.We call a sequence of contexts social context. This makes it difficult to predict local demand from users. In this paper, we propose a novel demand prediction engine that extracts local demand depending on social context and estimates what content will be requested there. To extract the demand, we use a log database and a pattern-matching technique in our prediction engine. To validate our prediction engine, we apply a prefetching service using the engine to a mobile content service.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Communications Workshops, ICC 2011 Workshops
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 IEEE International Conference on Communications Workshops, ICC 2011 Workshops - Kyoto, Japan
Duration: 2011 Jun 52011 Jun 9

Publication series

NameIEEE International Conference on Communications
ISSN (Print)0536-1486

Other

Other2011 IEEE International Conference on Communications Workshops, ICC 2011 Workshops
CountryJapan
CityKyoto
Period11/6/511/6/9

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Demand prediction based on social context for mobile content services'. Together they form a unique fingerprint.

  • Cite this

    Kubo, H., Shinkuma, R., Takahashi, T., Kasai, H., Yamaguchi, K., & Yates, R. (2011). Demand prediction based on social context for mobile content services. In 2011 IEEE International Conference on Communications Workshops, ICC 2011 Workshops [5963585] (IEEE International Conference on Communications). https://doi.org/10.1109/iccw.2011.5963585