This paper describes a new research proposal of multi-document summarization of dynamic content in web pages. Much information is lost in the Web due to the temporal character of web documents. Therefore adapting summarization techniques to the web genre is a promising task. The aim of our research is to provide methods for summarizing volatile content retrieved from collections of topically related web pages over defined time periods. The resulting summary ideally would reflect the most popular topics and concepts found in retrospective web collections. Because of the content and time diversities of web changes, it is necessary to apply different techniques than standard methods used for static documents. In this paper we propose an initial solution to this summarization problem. Our approach exploits temporal similarities between web pages by utilizing sliding window concept over dynamic parts of the collection.
|Number of pages||10|
|Journal||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Publication status||Published - 2004|
ASJC Scopus subject areas
- Computer Science(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Theoretical Computer Science