Summarization of texts found on the world wide web

Summaries of texts found on the World Wide Web are valuable. They help the user of a search engine to select information and are an aid for processing the vast amount of information found on the Web. This chapter describes the technologies that can be applied for summarizing the texts of Web pages. The focus is on technologies that currently generate the best results and are suited for the specific heterogeneous environment that makes up the World Wide Web. This chapter gives an overview of generic, query-biased and task-specific summarization, as well as single-document and multi-document summarization. Among the technologies that are discussed are semantic frame technologies, rhetorical structure analysis, learning discourse patterns, techniques relying upon lexical cohesion, and text clustering.

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