{"id":"https://openalex.org/W2538280969","doi":"https://doi.org/10.1109/nlpke.2011.6138182","title":"Study on meaningful string extraction algorithm for improving webpage classification","display_name":"Study on meaningful string extraction algorithm for improving webpage classification","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W2538280969","doi":"https://doi.org/10.1109/nlpke.2011.6138182","mag":"2538280969"},"language":"en","primary_location":{"id":"doi:10.1109/nlpke.2011.6138182","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2011.6138182","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 7th International Conference on Natural Language Processing and Knowledge Engineering","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066495421","display_name":"Jie Chen","orcid":"https://orcid.org/0000-0002-2196-9799"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Chen","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100402574","display_name":"Jian Li","orcid":"https://orcid.org/0000-0003-1138-7987"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Li","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091221734","display_name":"Hao Liao","orcid":"https://orcid.org/0000-0001-9152-4341"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Liao","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101056456","display_name":"Qingsheng Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingsheng Yuan","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109674238","display_name":"Xiuguo Bao","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuguo Bao","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"140","last_page":"145"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9725000262260437,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8764899969100952},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7488166093826294},{"id":"https://openalex.org/keywords/string","display_name":"String (physics)","score":0.6520642042160034},{"id":"https://openalex.org/keywords/document-clustering","display_name":"Document clustering","score":0.5719795227050781},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5390874743461609},{"id":"https://openalex.org/keywords/web-page","display_name":"Web page","score":0.49955177307128906},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.49324196577072144},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47117406129837036},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4632837176322937},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.45357951521873474},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.4304830729961395},{"id":"https://openalex.org/keywords/vector-space-model","display_name":"Vector space model","score":0.42284393310546875},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14925351738929749},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.06376650929450989}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8764899969100952},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7488166093826294},{"id":"https://openalex.org/C157486923","wikidata":"https://www.wikidata.org/wiki/Q1376436","display_name":"String (physics)","level":2,"score":0.6520642042160034},{"id":"https://openalex.org/C177937566","wikidata":"https://www.wikidata.org/wiki/Q4223102","display_name":"Document clustering","level":3,"score":0.5719795227050781},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5390874743461609},{"id":"https://openalex.org/C21959979","wikidata":"https://www.wikidata.org/wiki/Q36774","display_name":"Web page","level":2,"score":0.49955177307128906},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.49324196577072144},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47117406129837036},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4632837176322937},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.45357951521873474},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.4304830729961395},{"id":"https://openalex.org/C89686163","wikidata":"https://www.wikidata.org/wiki/Q1187982","display_name":"Vector space model","level":2,"score":0.42284393310546875},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14925351738929749},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.06376650929450989},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/nlpke.2011.6138182","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2011.6138182","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 7th International Conference on Natural Language Processing and Knowledge Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W37423176","https://openalex.org/W1481498866","https://openalex.org/W1907578970","https://openalex.org/W2014912547","https://openalex.org/W2036516910","https://openalex.org/W2132914434","https://openalex.org/W2145049651","https://openalex.org/W2159980296","https://openalex.org/W2439041746","https://openalex.org/W4255072837","https://openalex.org/W6659530292"],"related_works":["https://openalex.org/W1500125366","https://openalex.org/W2375068342","https://openalex.org/W3012376705","https://openalex.org/W2551770406","https://openalex.org/W2137763598","https://openalex.org/W2906422195","https://openalex.org/W1557970708","https://openalex.org/W1979094538","https://openalex.org/W4308344195","https://openalex.org/W2035932585"],"abstract_inverted_index":{"This":[0],"paper":[1],"shows":[2],"that":[3,116,127],"the":[4,113],"accuracy":[5],"of":[6],"webpage":[7,22,109],"classifiers":[8],"can":[9,87,149],"be":[10,150],"improved":[11],"by":[12,152],"extracting":[13,50],"meaningful":[14,51,89,96],"strings":[15,52,72,90],"with":[16,30,42,60,155],"an":[17],"unsupervised":[18],"clustering":[19,56,59,118,129,135,154,157],"method.":[20],"Since":[21],"classification":[23,29,111],"is":[24],"different":[25],"from":[26,91,158],"original":[27],"document":[28,55,110,117,134,156],"its":[31],"words":[32],"and":[33,37,57,112],"phrases":[34],"irregular,":[35],"massive":[36],"unlabeled":[38],"features,":[39,44],"to":[40,62,75,108],"cope":[41],"these":[43],"we":[45,86],"introduce":[46],"two":[47,79],"scenarios":[48,80],"for":[49],"based":[53],"on":[54,82],"term":[58,122,142],"multi-strategies":[61],"optimize":[63],"a":[64,145],"vector":[65],"space":[66],"model":[67],"(VSM).":[68],"First,":[69],"some":[70,159],"candidate":[71],"are":[73],"used":[74],"build":[76],"VSM;":[77],"then,":[78],"performance":[81,140,148],"VSM":[83],"respectively;":[84],"last,":[85],"extract":[88],"each":[92],"cluster.":[93],"So,":[94],"theses":[95],"string":[97],"may":[98],"represent":[99],"documents":[100],"comprehensively.":[101],"The":[102],"proposed":[103],"method":[104,130],"has":[105],"been":[106],"applied":[107],"results":[114],"show":[115],"works":[119],"better":[120,146],"than":[121],"clustering.":[123,143],"They":[124],"also":[125],"demonstrate":[126],"spectral":[128,153],"outperforms":[131],"k-means":[132],"in":[133,141],"case,":[136],"conversely,":[137],"make":[138],"reduce":[139],"However,":[144],"synthetic":[147],"obtained":[151],"experiments.":[160]},"counts_by_year":[{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}