Chinese Text Automatic Summarization Based on Affinity Propagation Cluster
Automatic summarization can help us accurately and efficiently obtain the information needed from the magnanimity information and has attracted more attention. In this paper, a new method for Chinese text summarization using the algorithm of affinity propagation cluster (APC) is presented. It is not...
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| creator | Changwei Zhao Qinke Peng Suhuan Sun |
| description | Automatic summarization can help us accurately and efficiently obtain the information needed from the magnanimity information and has attracted more attention. In this paper, a new method for Chinese text summarization using the algorithm of affinity propagation cluster (APC) is presented. It is not necessary to set the number of clusters and the initial representative exemplars in APC, so it can avoid the problems of local-optimal and instable clustering results caused by randomly selecting initial representative exemplars. And the algorithm has high computing efficiency. The results of the experiments show us that Chinese text automatic summarization based on APC has higher accuracy than that of other algorithms. APC is a suitable method for automatic text summarization. |
| doi_str_mv | 10.1109/FSKD.2009.302 |
| format | Conference Proceeding |
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In this paper, a new method for Chinese text summarization using the algorithm of affinity propagation cluster (APC) is presented. It is not necessary to set the number of clusters and the initial representative exemplars in APC, so it can avoid the problems of local-optimal and instable clustering results caused by randomly selecting initial representative exemplars. And the algorithm has high computing efficiency. The results of the experiments show us that Chinese text automatic summarization based on APC has higher accuracy than that of other algorithms. APC is a suitable method for automatic text summarization.</description><identifier>ISBN: 9780769537351</identifier><identifier>ISBN: 0769537359</identifier><identifier>DOI: 10.1109/FSKD.2009.302</identifier><identifier>LCCN: 2009906464</identifier><language>eng</language><publisher>IEEE</publisher><subject>Clustering algorithms ; Costs ; Fuzzy systems ; Knowledge engineering ; Laboratories ; Learning systems ; Machine learning algorithms ; Manufacturing systems ; Sun ; Systems engineering and theory</subject><ispartof>2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 2009, Vol.1, p.425-429</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5358556$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5358556$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Changwei Zhao</creatorcontrib><creatorcontrib>Qinke Peng</creatorcontrib><creatorcontrib>Suhuan Sun</creatorcontrib><title>Chinese Text Automatic Summarization Based on Affinity Propagation Cluster</title><title>2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery</title><addtitle>FSKD</addtitle><description>Automatic summarization can help us accurately and efficiently obtain the information needed from the magnanimity information and has attracted more attention. In this paper, a new method for Chinese text summarization using the algorithm of affinity propagation cluster (APC) is presented. It is not necessary to set the number of clusters and the initial representative exemplars in APC, so it can avoid the problems of local-optimal and instable clustering results caused by randomly selecting initial representative exemplars. And the algorithm has high computing efficiency. The results of the experiments show us that Chinese text automatic summarization based on APC has higher accuracy than that of other algorithms. APC is a suitable method for automatic text summarization.</description><subject>Clustering algorithms</subject><subject>Costs</subject><subject>Fuzzy systems</subject><subject>Knowledge engineering</subject><subject>Laboratories</subject><subject>Learning systems</subject><subject>Machine learning algorithms</subject><subject>Manufacturing systems</subject><subject>Sun</subject><subject>Systems engineering and theory</subject><isbn>9780769537351</isbn><isbn>0769537359</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotjk1LxDAYhAOyoK49evKSP9CaNJ_vsVbXrwWF7X1JN4lGtu3SpOD6662sc5kZHhgGoWtKCkoJ3K42r_dFSQgUjJRnKAOliZIgmGKCLtDlHwIiueTnKIvxi8xiwIHrC_RSf4beRYcb951wNaWhMyns8GbqOjOGn7kMPb4z0Vk8h8r70Id0xO_jcDAfJ1rvp5jceIUW3uyjy_59iZrVQ1M_5eu3x-e6WucBSMpboHrnjbQl4YIq8Ix6pQVY0K1qNbPGc-KtK61TzNrScG8IU9T71reSAVuim9NscM5tD2OYfx63ggkthGS_UYVOCw</recordid><startdate>200908</startdate><enddate>200908</enddate><creator>Changwei Zhao</creator><creator>Qinke Peng</creator><creator>Suhuan Sun</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200908</creationdate><title>Chinese Text Automatic Summarization Based on Affinity Propagation Cluster</title><author>Changwei Zhao ; Qinke Peng ; Suhuan Sun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-b918cfa6d2045179f31f7859d98b7b83daf40fde2de73dd2a4fa0371ffbfb6393</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Clustering algorithms</topic><topic>Costs</topic><topic>Fuzzy systems</topic><topic>Knowledge engineering</topic><topic>Laboratories</topic><topic>Learning systems</topic><topic>Machine learning algorithms</topic><topic>Manufacturing systems</topic><topic>Sun</topic><topic>Systems engineering and theory</topic><toplevel>online_resources</toplevel><creatorcontrib>Changwei Zhao</creatorcontrib><creatorcontrib>Qinke Peng</creatorcontrib><creatorcontrib>Suhuan Sun</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Changwei Zhao</au><au>Qinke Peng</au><au>Suhuan Sun</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Chinese Text Automatic Summarization Based on Affinity Propagation Cluster</atitle><btitle>2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery</btitle><stitle>FSKD</stitle><date>2009-08</date><risdate>2009</risdate><volume>1</volume><spage>425</spage><epage>429</epage><pages>425-429</pages><isbn>9780769537351</isbn><isbn>0769537359</isbn><abstract>Automatic summarization can help us accurately and efficiently obtain the information needed from the magnanimity information and has attracted more attention. In this paper, a new method for Chinese text summarization using the algorithm of affinity propagation cluster (APC) is presented. It is not necessary to set the number of clusters and the initial representative exemplars in APC, so it can avoid the problems of local-optimal and instable clustering results caused by randomly selecting initial representative exemplars. And the algorithm has high computing efficiency. The results of the experiments show us that Chinese text automatic summarization based on APC has higher accuracy than that of other algorithms. APC is a suitable method for automatic text summarization.</abstract><pub>IEEE</pub><doi>10.1109/FSKD.2009.302</doi><tpages>5</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Clustering algorithms Costs Fuzzy systems Knowledge engineering Laboratories Learning systems Machine learning algorithms Manufacturing systems Sun Systems engineering and theory |
| title | Chinese Text Automatic Summarization Based on Affinity Propagation Cluster |
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