Example-Based Chinese Text Filtering Model
This paper briefly describes the background of text filtering and proposes an example-based Chinese text filtering model. It analyzes the structure of the texts as example, extracts the keywords from the texts by means of the text hierarchical analysis presented in this paper, constructs the user pr...
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description | This paper briefly describes the background of text filtering and proposes an example-based Chinese text filtering model. It analyzes the structure of the texts as example, extracts the keywords from the texts by means of the text hierarchical analysis presented in this paper, constructs the user profiles which consist of the keywords above, and then filters the new text collections. Consequently, based on the user feedback, it expands the number of example texts, applies the approach of Latent Semantic Indexing to filter texts, and updates the user profiles to improve the efficiency of text filtering systems. |
doi_str_mv | 10.1007/978-3-540-46652-9_45 |
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It analyzes the structure of the texts as example, extracts the keywords from the texts by means of the text hierarchical analysis presented in this paper, constructs the user profiles which consist of the keywords above, and then filters the new text collections. Consequently, based on the user feedback, it expands the number of example texts, applies the approach of Latent Semantic Indexing to filter texts, and updates the user profiles to improve the efficiency of text filtering systems.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 3540669035</identifier><identifier>ISBN: 9783540669036</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 9783540466529</identifier><identifier>EISBN: 3540466525</identifier><identifier>DOI: 10.1007/978-3-540-46652-9_45</identifier><identifier>OCLC: 934978980</identifier><identifier>LCCallNum: Q162</identifier><language>eng</language><publisher>Germany: Springer Berlin / Heidelberg</publisher><subject>Applied sciences ; Artificial intelligence ; Computer science; control theory; systems ; Exact sciences and technology ; Latent Semantic Indexing ; Speech and sound recognition and synthesis. Linguistics ; Text filtering ; Text Hierarchical Analysis ; User Profiles</subject><ispartof>Internet Applications, 1999, Vol.1749, p.415-420</ispartof><rights>Springer-Verlag Berlin Heidelberg 1999</rights><rights>2000 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><relation>Lecture Notes in Computer Science</relation></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttps://ebookcentral.proquest.com/covers/3087476-l.jpg</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/978-3-540-46652-9_45$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/978-3-540-46652-9_45$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>309,310,779,780,784,789,790,793,4050,4051,27925,38255,41442,42511</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=1174987$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><contributor>Lee, Dik Lun</contributor><contributor>van Leeuwen, Jan</contributor><contributor>Hui, Lucas Chi-Kwong</contributor><contributor>Hui, Lucas Chi Kwong</contributor><contributor>Lee, Dik-Lun</contributor><creatorcontrib>Hongfei, Lin</creatorcontrib><creatorcontrib>Xuegang, Zhan</creatorcontrib><creatorcontrib>Tianshun, Yao</creatorcontrib><title>Example-Based Chinese Text Filtering Model</title><title>Internet Applications</title><description>This paper briefly describes the background of text filtering and proposes an example-based Chinese text filtering model. It analyzes the structure of the texts as example, extracts the keywords from the texts by means of the text hierarchical analysis presented in this paper, constructs the user profiles which consist of the keywords above, and then filters the new text collections. Consequently, based on the user feedback, it expands the number of example texts, applies the approach of Latent Semantic Indexing to filter texts, and updates the user profiles to improve the efficiency of text filtering systems.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Exact sciences and technology</subject><subject>Latent Semantic Indexing</subject><subject>Speech and sound recognition and synthesis. Linguistics</subject><subject>Text filtering</subject><subject>Text Hierarchical Analysis</subject><subject>User Profiles</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>3540669035</isbn><isbn>9783540669036</isbn><isbn>9783540466529</isbn><isbn>3540466525</isbn><fulltext>true</fulltext><rsrctype>book_chapter</rsrctype><creationdate>1999</creationdate><recordtype>book_chapter</recordtype><recordid>eNotUMtOwzAQNE8RSv-AQw6ckAy214_4CFULSEVcytlyki0NpEmIg1T-Hqd0LyvN7KxmhpBrzu44Y-bemowCVZJRqbUS1Dqpjsg0whDBPWaPScI15xRA2hNyORJaWwbqlCQMWBQZCecksZE3mc3YBZmG8MnigJBc8oTcznd-29VIH33AMp1tqgYDpivcDemiqgfsq-YjfW1LrK_I2drXAaeHPSHvi_lq9kyXb08vs4cl7YThA83RSGk498xbyL0UhfCF0tZwBGYiA9KLIs8wJkFQQsmyUFleCi24ZWsOE3Lz_7fzofD1uvdNUQXX9dXW97-OcyNtZuKZ-D8L3egRe5e37VdwnLmxQBcTO3CxErcvy40FRhEcfvft9w-GweGoKrAZel8XG9_FxMEBy6JT7aJMKgV_NP9rlA</recordid><startdate>1999</startdate><enddate>1999</enddate><creator>Hongfei, Lin</creator><creator>Xuegang, Zhan</creator><creator>Tianshun, Yao</creator><general>Springer Berlin / Heidelberg</general><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>FFUUA</scope><scope>IQODW</scope></search><sort><creationdate>1999</creationdate><title>Example-Based Chinese Text Filtering Model</title><author>Hongfei, Lin ; Xuegang, Zhan ; Tianshun, Yao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p271t-be744711a0a93ba42c2ac56971e30747134a2cb8e783e35254dc58bd262190f13</frbrgroupid><rsrctype>book_chapters</rsrctype><prefilter>book_chapters</prefilter><language>eng</language><creationdate>1999</creationdate><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computer science; control theory; systems</topic><topic>Exact sciences and technology</topic><topic>Latent Semantic Indexing</topic><topic>Speech and sound recognition and synthesis. Linguistics</topic><topic>Text filtering</topic><topic>Text Hierarchical Analysis</topic><topic>User Profiles</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hongfei, Lin</creatorcontrib><creatorcontrib>Xuegang, Zhan</creatorcontrib><creatorcontrib>Tianshun, Yao</creatorcontrib><collection>ProQuest Ebook Central - Book Chapters - Demo use only</collection><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hongfei, Lin</au><au>Xuegang, Zhan</au><au>Tianshun, Yao</au><au>Lee, Dik Lun</au><au>van Leeuwen, Jan</au><au>Hui, Lucas Chi-Kwong</au><au>Hui, Lucas Chi Kwong</au><au>Lee, Dik-Lun</au><format>book</format><genre>bookitem</genre><ristype>CHAP</ristype><atitle>Example-Based Chinese Text Filtering Model</atitle><btitle>Internet Applications</btitle><seriestitle>Lecture Notes in Computer Science</seriestitle><date>1999</date><risdate>1999</risdate><volume>1749</volume><spage>415</spage><epage>420</epage><pages>415-420</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>3540669035</isbn><isbn>9783540669036</isbn><eisbn>9783540466529</eisbn><eisbn>3540466525</eisbn><abstract>This paper briefly describes the background of text filtering and proposes an example-based Chinese text filtering model. It analyzes the structure of the texts as example, extracts the keywords from the texts by means of the text hierarchical analysis presented in this paper, constructs the user profiles which consist of the keywords above, and then filters the new text collections. Consequently, based on the user feedback, it expands the number of example texts, applies the approach of Latent Semantic Indexing to filter texts, and updates the user profiles to improve the efficiency of text filtering systems.</abstract><cop>Germany</cop><pub>Springer Berlin / Heidelberg</pub><doi>10.1007/978-3-540-46652-9_45</doi><oclcid>934978980</oclcid><tpages>6</tpages></addata></record> |
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language | eng |
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source | Springer Books |
subjects | Applied sciences Artificial intelligence Computer science control theory systems Exact sciences and technology Latent Semantic Indexing Speech and sound recognition and synthesis. Linguistics Text filtering Text Hierarchical Analysis User Profiles |
title | Example-Based Chinese Text Filtering Model |
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