Temporal multi-page summarization

Adam Jatowt*, Mitsuru Ishizuka

*この研究の対応する著者

研究成果: Article査読

13 被引用数 (Scopus)

抄録

With the increasing popularity of the Web, efficient approaches to the information overload are becoming more necessary. Summarization of web pages aims at detecting the most important contents from pages so that a user can obtain a compact version of a web document or a group of pages. Traditionally, summaries are constructed on static snapshots of web pages. However, web pages are dynamic objects that can change their contents anytime. In this paper, we discuss the research on temporal multi-document summarization in the Web. We analyze the temporal contents of topically related collections of web pages monitored for certain time intervals. The contents derived from the temporal versions of web documents are summarized to provide information on hot topics and popular events in the collection. We propose two summarization methods that use changing and static contents of web pages downloaded at defined time intervals. The first uses a sliding window mechanism and the second is based on analyzing the time series of the document frequencies of terms. Additionally, we introduce a novel sentence selection algorithm designed for time-dependent scenarios such as temporal summarization.

本文言語English
ページ(範囲)163-180
ページ数18
ジャーナルWeb Intelligence and Agent Systems
4
2
出版ステータスPublished - 2006
外部発表はい

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ ネットワークおよび通信
  • 計算理論と計算数学

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