{"id":"https://openalex.org/W2029671444","doi":"https://doi.org/10.1109/nlpke.2008.4906791","title":"Self-adaptive GA, quantitative semantic similarity measures and ontology-based text clustering","display_name":"Self-adaptive GA, quantitative semantic similarity measures and ontology-based text clustering","publication_year":2008,"publication_date":"2008-10-01","ids":{"openalex":"https://openalex.org/W2029671444","doi":"https://doi.org/10.1109/nlpke.2008.4906791","mag":"2029671444"},"language":"en","primary_location":{"id":"doi:10.1109/nlpke.2008.4906791","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2008.4906791","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 International Conference on Natural Language Processing and Knowledge Engineering","raw_type":"proceedings-article"},"type":"article","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/A5056318061","display_name":"Chengzhi Zhang","orcid":"https://orcid.org/0000-0001-9522-2914"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]},{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chengzhi Zhang","raw_affiliation_strings":["Department of Information Management, Nanjing University of Science & Technology, Institute of Sci & Tech Information of China, China","Dept. of Inf. Manage., Nanjing Univ. of Sci. & Technol., Nanjing"],"affiliations":[{"raw_affiliation_string":"Department of Information Management, Nanjing University of Science & Technology, Institute of Sci & Tech Information of China, China","institution_ids":["https://openalex.org/I200845125"]},{"raw_affiliation_string":"Dept. of Inf. Manage., Nanjing Univ. of Sci. & Technol., Nanjing","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023025722","display_name":"Wei Song","orcid":"https://orcid.org/0000-0003-0649-8850"},"institutions":[{"id":"https://openalex.org/I80611190","display_name":"Jeonbuk National University","ror":"https://ror.org/05q92br09","country_code":"KR","type":"education","lineage":["https://openalex.org/I80611190"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Wei Song","raw_affiliation_strings":["Division of Electronics and Information Engineering, Chonbuk National University, Jeonju, Jeonbuk, Korea","Div. of Electron. & Inf. Eng, Chonbuk Nat. Univ., Jeonju"],"affiliations":[{"raw_affiliation_string":"Division of Electronics and Information Engineering, Chonbuk National University, Jeonju, Jeonbuk, Korea","institution_ids":["https://openalex.org/I80611190"]},{"raw_affiliation_string":"Div. of Electron. & Inf. Eng, Chonbuk Nat. Univ., Jeonju","institution_ids":["https://openalex.org/I80611190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101607833","display_name":"Chenghua Li","orcid":"https://orcid.org/0000-0003-1407-7810"},"institutions":[{"id":"https://openalex.org/I80611190","display_name":"Jeonbuk National University","ror":"https://ror.org/05q92br09","country_code":"KR","type":"education","lineage":["https://openalex.org/I80611190"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chenghua Li","raw_affiliation_strings":["Division of Electronics and Information Engineering, Chonbuk National University, Jeonju, Jeonbuk, Korea","Div. of Electron. & Inf. Eng, Chonbuk Nat. Univ., Jeonju"],"affiliations":[{"raw_affiliation_string":"Division of Electronics and Information Engineering, Chonbuk National University, Jeonju, Jeonbuk, Korea","institution_ids":["https://openalex.org/I80611190"]},{"raw_affiliation_string":"Div. of Electron. & Inf. Eng, Chonbuk Nat. Univ., Jeonju","institution_ids":["https://openalex.org/I80611190"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101059302","display_name":"Wei Yu","orcid":"https://orcid.org/0000-0002-2847-7770"},"institutions":[{"id":"https://openalex.org/I4210104311","display_name":"Institute of Scientific and Technical Information of China","ror":"https://ror.org/01b2av652","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210104311","https://openalex.org/I4210120069","https://openalex.org/I4210127390"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Yu","raw_affiliation_strings":["Institute of Scientific & Technical Information of China, Beijing, China","Inst. of Sci. & Tech. Inf. of China, Beijing"],"affiliations":[{"raw_affiliation_string":"Institute of Scientific & Technical Information of China, Beijing, China","institution_ids":["https://openalex.org/I4210104311"]},{"raw_affiliation_string":"Inst. of Sci. & Tech. Inf. of China, Beijing","institution_ids":["https://openalex.org/I4210104311"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5056318061"],"corresponding_institution_ids":["https://openalex.org/I200845125","https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.07576777,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9948999881744385,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9948999881744385,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9926999807357788,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9922999739646912,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7952212691307068},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7763359546661377},{"id":"https://openalex.org/keywords/wordnet","display_name":"WordNet","score":0.7502106428146362},{"id":"https://openalex.org/keywords/vector-space-model","display_name":"Vector space model","score":0.6743468642234802},{"id":"https://openalex.org/keywords/document-clustering","display_name":"Document clustering","score":0.5798328518867493},{"id":"https://openalex.org/keywords/ontology","display_name":"Ontology","score":0.5754470825195312},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5166383385658264},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.5070662498474121},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5020980834960938},{"id":"https://openalex.org/keywords/thesaurus","display_name":"Thesaurus","score":0.4993422031402588},{"id":"https://openalex.org/keywords/latent-semantic-analysis","display_name":"Latent semantic analysis","score":0.48658931255340576},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4441569447517395},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.42219704389572144},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.36498066782951355}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7952212691307068},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7763359546661377},{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.7502106428146362},{"id":"https://openalex.org/C89686163","wikidata":"https://www.wikidata.org/wiki/Q1187982","display_name":"Vector space model","level":2,"score":0.6743468642234802},{"id":"https://openalex.org/C177937566","wikidata":"https://www.wikidata.org/wiki/Q4223102","display_name":"Document clustering","level":3,"score":0.5798328518867493},{"id":"https://openalex.org/C25810664","wikidata":"https://www.wikidata.org/wiki/Q44325","display_name":"Ontology","level":2,"score":0.5754470825195312},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5166383385658264},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.5070662498474121},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5020980834960938},{"id":"https://openalex.org/C2778698081","wikidata":"https://www.wikidata.org/wiki/Q179797","display_name":"Thesaurus","level":2,"score":0.4993422031402588},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.48658931255340576},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4441569447517395},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.42219704389572144},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36498066782951355},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/nlpke.2008.4906791","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2008.4906791","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 International Conference on Natural Language Processing and Knowledge Engineering","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.rclis.org:12400","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401228","display_name":"E-LIS Repository (University of Naples Federico II)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I71267560","host_organization_name":"University of Naples Federico II","host_organization_lineage":["https://openalex.org/I71267560"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"},{"id":"pmh:oai:hispana.mcu.es:6652854","is_oa":false,"landing_page_url":"https://hispana.mcu.es/es/registros/registro.do?tipoRegistro=MTD&idBib=6652854","pdf_url":null,"source":{"id":"https://openalex.org/S4377196108","display_name":"Hispana","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W81068815","https://openalex.org/W130742730","https://openalex.org/W1736099096","https://openalex.org/W1859953786","https://openalex.org/W1997600725","https://openalex.org/W2051224630","https://openalex.org/W2071965987","https://openalex.org/W2073503732","https://openalex.org/W2073849744","https://openalex.org/W2081580037","https://openalex.org/W2102660810","https://openalex.org/W2107903523","https://openalex.org/W2117805756","https://openalex.org/W2120482366","https://openalex.org/W2123457740","https://openalex.org/W2133517430","https://openalex.org/W2134145060","https://openalex.org/W2162965720","https://openalex.org/W2302947639","https://openalex.org/W2950225692","https://openalex.org/W6603320342","https://openalex.org/W6638874690","https://openalex.org/W6677712588","https://openalex.org/W6678129117","https://openalex.org/W6678220738"],"related_works":["https://openalex.org/W2043952800","https://openalex.org/W2047143235","https://openalex.org/W2957377172","https://openalex.org/W2165693052","https://openalex.org/W2113471940","https://openalex.org/W2569513598","https://openalex.org/W2907883452","https://openalex.org/W2251695880","https://openalex.org/W101928771","https://openalex.org/W2052466360"],"abstract_inverted_index":{"As":[0],"the":[1,13,49,67,71,78,82,103,113,116,123,137,140,151,154,160,166,172,175],"common":[2],"clustering":[3,29,124,132,156,176],"algorithms":[4],"use":[5],"vector":[6],"space":[7],"model":[8,101],"(VSM)":[9],"to":[10,43,88],"represent":[11],"document,":[12],"conceptual":[14],"relationships":[15],"between":[16],"related":[17],"terms":[18],"which":[19],"do":[20],"not":[21],"co-occur":[22],"literally":[23],"are":[24,120],"ignored.":[25],"A":[26],"genetic":[27],"algorithm-based":[28],"technique,":[30],"named":[31],"GA":[32,131,155,168],"clustering,":[33],"in":[34,40,90,106,122,134],"conjunction":[35,135],"with":[36,136,146],"ontology":[37,50],"is":[38,85,169],"proposed":[39,158],"this":[41,45,107],"article":[42],"overcome":[44],"problem.":[46],"In":[47],"general,":[48],"measures":[51],"can":[52],"be":[53],"partitioned":[54],"into":[55],"two":[56,110],"categories:":[57],"thesaurus-based":[58,79,138],"methods":[59],"and":[60,70,139,165],"corpus-based":[61,83,104],"methods.":[62],"We":[63,93],"take":[64],"advantage":[65],"of":[66,75,115,153,174],"hierarchical":[68],"structure":[69],"broad":[72],"coverage":[73],"taxonomy":[74],"Wordnet":[76],"as":[77,102],"ontology.":[80],"However,":[81],"method":[84,105],"rather":[86],"complicated":[87],"handle":[89],"practical":[91],"application.":[92],"propose":[94],"a":[95],"transformed":[96],"latent":[97],"semantic":[98],"analysis":[99],"(LSA)":[100],"paper.":[108],"Moreover,":[109,150],"hybrid":[111],"strategies,":[112],"combinations":[114],"various":[117],"similarity":[118,148],"measures,":[119],"implemented":[121],"experiments.":[125],"The":[126],"results":[127],"show":[128],"that":[129,145],"our":[130],"algorithm,":[133],"LSA-based":[141],"method,":[142],"apparently":[143],"outperforms":[144],"other":[147],"measures.":[149],"superiority":[152],"algorithm":[157,164],"over":[159],"commonly":[161],"used":[162],"k-means":[163],"standard":[167],"demonstrated":[170],"by":[171],"improvements":[173],"performance.":[177]},"counts_by_year":[{"year":2017,"cited_by_count":2},{"year":2013,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}