{"id":"https://openalex.org/W2117851866","doi":"https://doi.org/10.1145/2492517.2500317","title":"Enhancing text clustering model based on truncated singular value decomposition, fuzzy art and cross validation","display_name":"Enhancing text clustering model based on truncated singular value decomposition, fuzzy art and cross validation","publication_year":2013,"publication_date":"2013-08-25","ids":{"openalex":"https://openalex.org/W2117851866","doi":"https://doi.org/10.1145/2492517.2500317","mag":"2117851866"},"language":"en","primary_location":{"id":"doi:10.1145/2492517.2500317","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2492517.2500317","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining","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/A5040335868","display_name":"Choukri Djellali","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Choukri Djellali","raw_affiliation_strings":["Laboratory for research on technology for ecommerce, Montreal (Quebec)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory for research on technology for ecommerce, Montreal (Quebec)","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5040335868"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2288,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.50834244,"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":"1078","last_page":"1083"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9983000159263611,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9983000159263611,"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":0.9958999752998352,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.994700014591217,"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/singular-value-decomposition","display_name":"Singular value decomposition","score":0.6887226104736328},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5574455857276917},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.5571399927139282},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5512184500694275},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5511929988861084},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.4590117335319519},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4176813066005707},{"id":"https://openalex.org/keywords/cross-validation","display_name":"Cross-validation","score":0.41733989119529724},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3690701127052307},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17864447832107544}],"concepts":[{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.6887226104736328},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5574455857276917},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.5571399927139282},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5512184500694275},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5511929988861084},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.4590117335319519},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4176813066005707},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.41733989119529724},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3690701127052307},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17864447832107544},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2492517.2500317","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2492517.2500317","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1490760466","https://openalex.org/W1501500081","https://openalex.org/W1530552487","https://openalex.org/W1996463707","https://openalex.org/W2012611887","https://openalex.org/W2048720636","https://openalex.org/W2050436265","https://openalex.org/W2052914920","https://openalex.org/W2067278453","https://openalex.org/W2073646237","https://openalex.org/W2075705726","https://openalex.org/W2076769479","https://openalex.org/W2111229253","https://openalex.org/W2116506662","https://openalex.org/W2117341849","https://openalex.org/W2127097372","https://openalex.org/W2127969535","https://openalex.org/W2129910427","https://openalex.org/W2134043922","https://openalex.org/W2134823866","https://openalex.org/W2142557068","https://openalex.org/W2148541040","https://openalex.org/W2153233077","https://openalex.org/W2156108033","https://openalex.org/W2161163382","https://openalex.org/W2165612380","https://openalex.org/W2167987975","https://openalex.org/W2169738360","https://openalex.org/W2170413589","https://openalex.org/W2563104793"],"related_works":["https://openalex.org/W1999627569","https://openalex.org/W763609066","https://openalex.org/W1849651648","https://openalex.org/W3107474891","https://openalex.org/W2359631251","https://openalex.org/W2348097614","https://openalex.org/W2165238519","https://openalex.org/W1965757845","https://openalex.org/W37155842","https://openalex.org/W2032989665"],"abstract_inverted_index":{"Numerical":[0],"schemes":[1,43],"research":[2],"on":[3],"clustering":[4,39,72],"model":[5,80],"has":[6],"been":[7],"quite":[8],"intensive":[9],"in":[10,59],"the":[11,26,60,71,88,92],"past":[12],"decade.":[13],"The":[14,74],"difficulties":[15],"associated":[16],"with":[17,87],"curse":[18],"of":[19,34,51,56,95],"dimensionality":[20],"and":[21,32,40,83],"cost":[22],"functions":[23],"to":[24,46,69],"reflect":[25],"general":[27],"knowledge":[28],"about":[29],"internal":[30],"structures":[31],"distributions":[33],"target":[35],"data.":[36],"Traditional":[37],"computational":[38],"variables":[41],"selection":[42],"are":[44],"struggling":[45],"estimate":[47],"at":[48],"high":[49],"level":[50],"accuracy":[52],"for":[53],"this":[54],"type":[55],"problem.":[57],"Hence,":[58],"present":[61],"study,":[62],"a":[63],"novel":[64],"semantic-based":[65],"scheme":[66],"was":[67],"proposed":[68],"enhance":[70],"accuracy.":[73],"results":[75],"show":[76],"that":[77],"our":[78,96],"conceptual":[79],"is":[81],"automatic":[82],"optimal.":[84],"Good":[85],"comparisons":[86],"experimental":[89],"studies":[90],"demonstrate":[91],"multidisciplinary":[93],"applications":[94],"approach.":[97]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
