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Microsoft Word - E070119（11页）_1_.doc
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Document Date: 2012-12-14 16:12:29

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File Size: 114,54 KB

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City

Sapporo / Beijing / /

Company

IBM / Computational Information Systems / /

Country

Japan / United States / China / /

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Event

Product Recall / Product Issues / /

Facility

Peking University / Chapel Hill / Institute of Scientific / Lingnan University / Nanjing University of Science / /

IndustryTerm

keyword extraction tools / automatic processing / keyword extraction algorithm / Maximum entropy learning algorithm / text mining applications / /

Organization

Nanjing University of Science & Technology / Nanjing / Hong Kong Department of Computer Science and Technolog / Institute of Scientific & Technical Information of China / Ministry of Science & Technology of China / SVM CRF / Lingnan University / IDF / Information Center for Social Sciences of RUC / Youth Research Support Fund / Department of Management / Ministry of Education / Jiangsu Education Commission / Education Ministry / China Department of Information Management / American Society for Information Science / Peking University / Beijing / /

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Position

general / general and domain-specific / Keyword Extraction Full General and Domain-specific General / General / Corresponding author / /

Product

SegTag / comparison / CRF-based / /

ProvinceOrState

Jiangsu Province / /

PublishedMedium

Machine Learning / /

Technology

Natural Language Processing / Viterbi algorithm / machine learning / html / keyword extraction algorithm / Technology of China / Maximum entropy learning algorithm / be efficiently determined using the Viterbi algorithm / /

URL

http /

SocialTag