News Miner: a Tool for Information Retrieval

نویسندگان

  • Alberto Sillitti
  • Marco Scotto
  • Giancarlo Succi
  • Tullio Vernazza
چکیده

The World Wide Web is the richest source of information today available, but only a small set of these data are interesting for users. The overload of information can produce a waste of time rather than a real benefit. Moreover, information is spread all over the Web and its structure makes difficult to extract relevant data in automated ways. This paper presents News Miner (NM) a tool for news extraction, integration, and presentation. The discussion highlights information retrieval and integration issues based on users’ preferences. A case study presents news integration collecting data from three search engines.

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تاریخ انتشار 2002