Generating an event arrangement for understanding news articles on the web

Authors:
Norifumi Hirata;Shun Shiramatsu;Tadachika Ozono;Toramatsu Shintani
Affiliations:
Dept. of Computer Science and Engineering, Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Aichi, Japan;Dept. of Computer Science and Engineering, Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Aichi, Japan;Dept. of Computer Science and Engineering, Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Aichi, Japan;Dept. of Computer Science and Engineering, Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Aichi, Japan
Venue:
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part II
Year:
2010

Citing 6
Cited 0

Fast and effective text mining using linear-time document clustering

KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)
Text clustering with extended user feedback

SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Incremental hierarchical clustering of text documents

CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Extracting related named entities from blogosphere for event mining

Proceedings of the 2nd international conference on Ubiquitous information management and communication
Text classification by labeling words

AAAI'04 Proceedings of the 19th national conference on Artifical intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

We propose a new event arrangement system for Web news browsing based on analyzing past news articles related to the browsing-targeted article. Since relevant events are important for understanding news articles, we propose an event arrangement system based on making a connection between the relevant events and providing sequences of those events. When a user chooses an event from candidate events extracted on the basis of time series and important words, the system generates other events related to the chosen one. The system enables a user to find topic sequences suiting one's interest and to closely understand news articles.