Rule extraction from blog using Inductive logic Programming

Noriaki Chikara, Miyuki Koshimura, Hiroshi Fujita, Ryuzo Hasegawa

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

1 Citation (Scopus)

Abstract

Information recommender system attempts to present information that is likely to be useful for the user. Showing recommendation reason is an important role of the system. However, current recommender systems give only simple or quantitative reasons for the recommendation. In this paper, we aim at giving precise and non-quantitative reasons which are also easy to understand. We make use of formulas in first-order predicate logic for explaining the reason. In order to build such formulas, we use Inductive logic Programming. We succeeded to extract several useful formulas from blogs.

Original languageEnglish
Title of host publicationProceedings - 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2010
Pages269-272
Number of pages4
DOIs
Publication statusPublished - 2010
Event2010 3rd IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2010 - Toronto, ON, Canada
Duration: Aug 31 2010Sept 3 2010

Publication series

NameProceedings - 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2010

Other

Other2010 3rd IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2010
Country/TerritoryCanada
CityToronto, ON
Period8/31/109/3/10

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Software

Fingerprint

Dive into the research topics of 'Rule extraction from blog using Inductive logic Programming'. Together they form a unique fingerprint.

Cite this