Loading…
An Enhanced Wu-Huberman Algorithm with Pole Point Selection Strategy
The Wu-Huberman clustering is a typical linear algorithm among many clustering algorithms, which illustrates data points relationship as an artificial “circuit” and then applies the Kirchhoff equations to get the voltage value on the complex circuit. However, the performance of the algorithm is cruc...
Saved in:
| Published in: | Abstract and Applied Analysis 2013-01, Vol.2013 (2013), p.405-410-743 |
|---|---|
| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Subjects: | |
| Citations: | Items that this one cites |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| cited_by | |
|---|---|
| cites | cdi_FETCH-LOGICAL-a581t-9f391fdde5ab7c0a7960761cb7c1bc1c8c277b36077fb3547e04ed35bb5c2a243 |
| container_end_page | 410-743 |
| container_issue | 2013 |
| container_start_page | 405 |
| container_title | Abstract and Applied Analysis |
| container_volume | 2013 |
| creator | Sun, Yan Ding, Shuxue |
| description | The Wu-Huberman clustering is a typical linear algorithm among many clustering algorithms, which illustrates data points relationship as an artificial “circuit” and then applies the Kirchhoff equations to get the voltage value on the complex circuit. However, the performance of the algorithm is crucially dependent on the selection of pole points. In this paper, we present a novel pole point selection strategy for the Wu-Huberman algorithm (named as PSWH algorithm), which aims at preserving the merit and increasing the robustness of the algorithm. The pole point selection strategy is proposed to filter the pole point by introducing sparse rate. Experiments results demonstrate that the PSWH algorithm is significantly improved in clustering accuracy and efficiency compared with the original Wu-Huberman algorithm. |
| doi_str_mv | 10.1155/2013/589386 |
| format | article |
| fullrecord | <record><control><sourceid>gale_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_6193aa5c02754a24973d3c61e477f432</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A369794520</galeid><airiti_id>P20160825001_201312_201609070065_201609070065_405_410_743</airiti_id><doaj_id>oai_doaj_org_article_6193aa5c02754a24973d3c61e477f432</doaj_id><sourcerecordid>A369794520</sourcerecordid><originalsourceid>FETCH-LOGICAL-a581t-9f391fdde5ab7c0a7960761cb7c1bc1c8c277b36077fb3547e04ed35bb5c2a243</originalsourceid><addsrcrecordid>eNqFkk1r3DAQhk1poWnaU88FQy8lxcnoy7JuXbZpE1joQhp6FLIs72qxpVS2Cfn3nV0vW9JLMfp69c4zHjFZ9p7AJSFCXFEg7EpUilXli-yMlJUsgIN6iXuoRMGYFK-zN8OwAwAmOT_Lvi5Cfh22JljX5L-m4maqXepNyBfdJiY_bvv8Eed8HTuHkw9jfuc6Z0cfQ343JjO6zdPb7FVrusG9O67n2f2365_Lm2L14_vtcrEqjKjIWKiWKdI2jROmlhaMVCXIklg8kNoSW1kqZc1QlG3NBJcOuGuYqGthqaGcnWe3M7eJZqcfku9NetLReH0QYtpok0ZvO6dLopgxwgKVgmOskqxhtiSOI5wziqwvM-shxR3W4ybb-eYZdHm_OqrHxRijCVOMI04qRHw6IX5Pbhh17wfrus4EF6dBE8EIUFYesn38x7qLUwr4WJpwWgGhVAK6LmfXxmAJPrQRH9ji17je2xhc61FfsFJJxQXdB3yeA2yKw5Bce_p_AnrfEXrfEXruCHRfzO6tD4159P8xf5jNDi2uNSczrxjh-9Tr-d54bBP_t541UkqoqAAgByKh-iApkACleH7ggAPzS87YHz6E0Sw</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1428012270</pqid></control><display><type>article</type><title>An Enhanced Wu-Huberman Algorithm with Pole Point Selection Strategy</title><source>Wiley Online Library Open Access</source><source>Publicly Available Content Database</source><creator>Sun, Yan ; Ding, Shuxue</creator><contributor>Xie, Fuding</contributor><creatorcontrib>Sun, Yan ; Ding, Shuxue ; Xie, Fuding</creatorcontrib><description>The Wu-Huberman clustering is a typical linear algorithm among many clustering algorithms, which illustrates data points relationship as an artificial “circuit” and then applies the Kirchhoff equations to get the voltage value on the complex circuit. However, the performance of the algorithm is crucially dependent on the selection of pole points. In this paper, we present a novel pole point selection strategy for the Wu-Huberman algorithm (named as PSWH algorithm), which aims at preserving the merit and increasing the robustness of the algorithm. The pole point selection strategy is proposed to filter the pole point by introducing sparse rate. Experiments results demonstrate that the PSWH algorithm is significantly improved in clustering accuracy and efficiency compared with the original Wu-Huberman algorithm.</description><identifier>ISSN: 1085-3375</identifier><identifier>EISSN: 1687-0409</identifier><identifier>DOI: 10.1155/2013/589386</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Limiteds</publisher><subject>Accuracy ; Algorithms ; Circuits ; Clustering ; Clustering (Computers) ; Community ; Data mining ; Mathematical analysis ; Mathematical research ; Poles ; Robustness ; Statistical analysis ; Statistical methods ; Strategy ; Studies ; Voltage</subject><ispartof>Abstract and Applied Analysis, 2013-01, Vol.2013 (2013), p.405-410-743</ispartof><rights>Copyright © 2013 Yan Sun and Shuxue Ding.</rights><rights>COPYRIGHT 2013 John Wiley & Sons, Inc.</rights><rights>Copyright © 2013 Yan Sun and Shuxue Ding. Yan Sun et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</rights><rights>Copyright 2013 Hindawi Publishing Corporation</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-a581t-9f391fdde5ab7c0a7960761cb7c1bc1c8c277b36077fb3547e04ed35bb5c2a243</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1428012270/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1428012270?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,25753,27924,27925,37012,37013,44590,75126</link.rule.ids></links><search><contributor>Xie, Fuding</contributor><creatorcontrib>Sun, Yan</creatorcontrib><creatorcontrib>Ding, Shuxue</creatorcontrib><title>An Enhanced Wu-Huberman Algorithm with Pole Point Selection Strategy</title><title>Abstract and Applied Analysis</title><description>The Wu-Huberman clustering is a typical linear algorithm among many clustering algorithms, which illustrates data points relationship as an artificial “circuit” and then applies the Kirchhoff equations to get the voltage value on the complex circuit. However, the performance of the algorithm is crucially dependent on the selection of pole points. In this paper, we present a novel pole point selection strategy for the Wu-Huberman algorithm (named as PSWH algorithm), which aims at preserving the merit and increasing the robustness of the algorithm. The pole point selection strategy is proposed to filter the pole point by introducing sparse rate. Experiments results demonstrate that the PSWH algorithm is significantly improved in clustering accuracy and efficiency compared with the original Wu-Huberman algorithm.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Circuits</subject><subject>Clustering</subject><subject>Clustering (Computers)</subject><subject>Community</subject><subject>Data mining</subject><subject>Mathematical analysis</subject><subject>Mathematical research</subject><subject>Poles</subject><subject>Robustness</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>Strategy</subject><subject>Studies</subject><subject>Voltage</subject><issn>1085-3375</issn><issn>1687-0409</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqFkk1r3DAQhk1poWnaU88FQy8lxcnoy7JuXbZpE1joQhp6FLIs72qxpVS2Cfn3nV0vW9JLMfp69c4zHjFZ9p7AJSFCXFEg7EpUilXli-yMlJUsgIN6iXuoRMGYFK-zN8OwAwAmOT_Lvi5Cfh22JljX5L-m4maqXepNyBfdJiY_bvv8Eed8HTuHkw9jfuc6Z0cfQ343JjO6zdPb7FVrusG9O67n2f2365_Lm2L14_vtcrEqjKjIWKiWKdI2jROmlhaMVCXIklg8kNoSW1kqZc1QlG3NBJcOuGuYqGthqaGcnWe3M7eJZqcfku9NetLReH0QYtpok0ZvO6dLopgxwgKVgmOskqxhtiSOI5wziqwvM-shxR3W4ybb-eYZdHm_OqrHxRijCVOMI04qRHw6IX5Pbhh17wfrus4EF6dBE8EIUFYesn38x7qLUwr4WJpwWgGhVAK6LmfXxmAJPrQRH9ji17je2xhc61FfsFJJxQXdB3yeA2yKw5Bce_p_AnrfEXrfEXruCHRfzO6tD4159P8xf5jNDi2uNSczrxjh-9Tr-d54bBP_t541UkqoqAAgByKh-iApkACleH7ggAPzS87YHz6E0Sw</recordid><startdate>20130101</startdate><enddate>20130101</enddate><creator>Sun, Yan</creator><creator>Ding, Shuxue</creator><general>Hindawi Limiteds</general><general>Hindawi Puplishing Corporation</general><general>Hindawi Publishing Corporation</general><general>John Wiley & Sons, Inc</general><general>Hindawi Limited</general><scope>188</scope><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>KR7</scope><scope>L6V</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>DOA</scope></search><sort><creationdate>20130101</creationdate><title>An Enhanced Wu-Huberman Algorithm with Pole Point Selection Strategy</title><author>Sun, Yan ; Ding, Shuxue</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a581t-9f391fdde5ab7c0a7960761cb7c1bc1c8c277b36077fb3547e04ed35bb5c2a243</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Circuits</topic><topic>Clustering</topic><topic>Clustering (Computers)</topic><topic>Community</topic><topic>Data mining</topic><topic>Mathematical analysis</topic><topic>Mathematical research</topic><topic>Poles</topic><topic>Robustness</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><topic>Strategy</topic><topic>Studies</topic><topic>Voltage</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Sun, Yan</creatorcontrib><creatorcontrib>Ding, Shuxue</creatorcontrib><collection>Airiti Library</collection><collection>الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals</collection><collection>معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete</collection><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</collection><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Database (1962 - current)</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>Middle East & Africa Database</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>Directory of Open Access Journals</collection><jtitle>Abstract and Applied Analysis</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Sun, Yan</au><au>Ding, Shuxue</au><au>Xie, Fuding</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Enhanced Wu-Huberman Algorithm with Pole Point Selection Strategy</atitle><jtitle>Abstract and Applied Analysis</jtitle><date>2013-01-01</date><risdate>2013</risdate><volume>2013</volume><issue>2013</issue><spage>405</spage><epage>410-743</epage><pages>405-410-743</pages><issn>1085-3375</issn><eissn>1687-0409</eissn><abstract>The Wu-Huberman clustering is a typical linear algorithm among many clustering algorithms, which illustrates data points relationship as an artificial “circuit” and then applies the Kirchhoff equations to get the voltage value on the complex circuit. However, the performance of the algorithm is crucially dependent on the selection of pole points. In this paper, we present a novel pole point selection strategy for the Wu-Huberman algorithm (named as PSWH algorithm), which aims at preserving the merit and increasing the robustness of the algorithm. The pole point selection strategy is proposed to filter the pole point by introducing sparse rate. Experiments results demonstrate that the PSWH algorithm is significantly improved in clustering accuracy and efficiency compared with the original Wu-Huberman algorithm.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Limiteds</pub><doi>10.1155/2013/589386</doi><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1085-3375 |
| ispartof | Abstract and Applied Analysis, 2013-01, Vol.2013 (2013), p.405-410-743 |
| issn | 1085-3375 1687-0409 |
| language | eng |
| recordid | cdi_doaj_primary_oai_doaj_org_article_6193aa5c02754a24973d3c61e477f432 |
| source | Wiley Online Library Open Access; Publicly Available Content Database |
| subjects | Accuracy Algorithms Circuits Clustering Clustering (Computers) Community Data mining Mathematical analysis Mathematical research Poles Robustness Statistical analysis Statistical methods Strategy Studies Voltage |
| title | An Enhanced Wu-Huberman Algorithm with Pole Point Selection Strategy |
| url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T10%3A47%3A06IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=An%20Enhanced%20Wu-Huberman%20Algorithm%20with%20Pole%20Point%20Selection%20Strategy&rft.jtitle=Abstract%20and%20Applied%20Analysis&rft.au=Sun,%20Yan&rft.date=2013-01-01&rft.volume=2013&rft.issue=2013&rft.spage=405&rft.epage=410-743&rft.pages=405-410-743&rft.issn=1085-3375&rft.eissn=1687-0409&rft_id=info:doi/10.1155/2013/589386&rft_dat=%3Cgale_doaj_%3EA369794520%3C/gale_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-a581t-9f391fdde5ab7c0a7960761cb7c1bc1c8c277b36077fb3547e04ed35bb5c2a243%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1428012270&rft_id=info:pmid/&rft_galeid=A369794520&rft_airiti_id=P20160825001_201312_201609070065_201609070065_405_410_743&rfr_iscdi=true |