News Recommendation based on Semantic Relations between Events

نویسندگان

  • Ryohei Yoko
  • Takahiro Kawamura
  • Yuichi Sei
  • Yasuyuki Tahara
  • Akihiko Ohsuga
چکیده

In recent years, “News Curation Services” that recommend news articles on the internet to user have been popular. In this study, we propose a new “News Curation Service” that collects and recommends novel articles by using semantic relationships between events in the news articles that a user feels interest. The semantic relationships between events are represented by Linked Data. In order to recommend the news articles to the user, we create search queries by using the sentence structure features. Finally, we collect the news articles on the internet and recommend the articles to the user.

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تاریخ انتشار 2014