Fostering Multi-Modal Summarization for Trend Information

Authors:
Tsuneaki Kato;Mitsunori Matsushita;Noriko Kando
Affiliations:
The University of Tokyo, 3-8-1 Komaba, Meguro-ku, Tokyo 153-8902, Japan;NTT Communication Science Laboratories, NTT Corp., 2-4 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0237, Japan;National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, Tokyo 101-8430, Japan
Venue:
KES '07 Knowledge-Based Intelligent Information and Engineering Systems and the XVII Italian Workshop on Neural Networks on Proceedings of the 11th International Conference
Year:
2007

Citing 6
Cited 0

Data characterization for intelligent graphics presentation

CHI '90 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Information visualization

Readings in information visualization
Robust temporal processing of news

ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
TREC: Experiment and Evaluation in Information Retrieval (Digital Libraries and Electronic Publishing)

TREC: Experiment and Evaluation in Information Retrieval (Digital Libraries and Electronic Publishing)
QuestionBank: creating a corpus of parse-annotated questions

ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Preemptive information extraction using unrestricted relation discovery

HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics

Quantified Score

Hi-index	0.00

Visualization

Abstract

It is more important than ever to be able to extract relevant information and to understand or review its content quickly. Spotting trends is one such way of understanding or reviewing. We propose multi-modal summarization for trend information as a new technology to help this activity. We also describe the design of a data set that will foster research in the field, and introduce an ongoing unique workshop using this data set.