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Syskill & Webert: Identifying interesting web sites Michael Pazzani, Jack Muramatsu & Daniel Billsus Department of Information and Computer Science University of California, Irvine Irvine, CA[removed]removed]
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Document Date: 1998-05-19 11:59:54

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File Size: 51,18 KB

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City

Cambridge / Lake Tahoe / New York / /

Company

ACM Special Interest Group / Neural Networks / MIT Press / Case / John Wiley & Sons / /

/

Facility

Prentice Hall / Computer Science University of California / Institute of Radio Engineers / /

IndustryTerm

multi-layer networks / machine learning algorithms / search domain / default algorithm / Web search engine / Web search engines / information retrieval systems / classification technology / nearest neighbor algorithm / particular web page / Web Agent / learning algorithm / learning algorithms / software agent / /

MarketIndex

LYCOS / /

Organization

Information and Computer Science University / National Science Foundation / MIT / Institute of Radio Engineers / Western Electronic Show and Convention / IDF / Center for Machine Translation Proceedings / Muramatsu & Daniel Billsus Department of Information / University of California / Irvine / American Society for Information Science / /

Person

Duda / Daniel Billsus / Jack Muramatsu / Michael Pazzani / /

/

Position

editor / General / particular author / Harper / /

ProgrammingLanguage

HTML / /

ProvinceOrState

California / /

PublishedMedium

Machine Learning / /

Technology

learning algorithm / IR algorithms / machine learning algorithms / artificial intelligence / jpeg / default algorithm / Machine Translation / applying machine learning algorithms / five learning algorithms / nearest neighbor algorithm / underlying classification technology / Learning algorithms / search engine / machine learning / underlying technology / HTML / /

URL

http /

SocialTag