{"id":"https://openalex.org/W2078975293","doi":"https://doi.org/10.4304/jcp.9.6.1316-1324","title":"Spectral Clustering with Neighborhood Attribute Reduction Based on Information Entropy","display_name":"Spectral Clustering with Neighborhood Attribute Reduction Based on Information Entropy","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W2078975293","doi":"https://doi.org/10.4304/jcp.9.6.1316-1324","mag":"2078975293"},"language":"en","primary_location":{"id":"doi:10.4304/jcp.9.6.1316-1324","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jcp.9.6.1316-1324","pdf_url":null,"source":{"id":"https://openalex.org/S77894049","display_name":"Journal of Computers","issn_l":"1796-203X","issn":["1796-203X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computers","raw_type":"journal-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/A5037232889","display_name":"Hongjie Jia","orcid":"https://orcid.org/0000-0002-3354-5184"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hongjie Jia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082274996","display_name":"Shifei Ding","orcid":"https://orcid.org/0000-0002-1391-2717"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shifei Ding","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100710715","display_name":"Heng Ma","orcid":"https://orcid.org/0000-0002-7667-922X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Heng Ma","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5005227620","display_name":"Wanqiu Xing","orcid":"https://orcid.org/0000-0002-1714-1809"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wanqiu Xing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3574,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.64299938,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"9","issue":"6","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11063","display_name":"Rough Sets and Fuzzy Logic","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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":0.9789000153541565,"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":0.6319462060928345},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5642333030700684},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5218914151191711},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.4983079433441162},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4950791895389557},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4728688895702362},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.46438679099082947},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4025503695011139},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.39075347781181335},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.12262853980064392},{"id":"https://openalex.org/keywords/thermodynamics","display_name":"Thermodynamics","score":0.05134320259094238},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.04965829849243164}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6319462060928345},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5642333030700684},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5218914151191711},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.4983079433441162},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4950791895389557},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4728688895702362},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46438679099082947},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4025503695011139},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39075347781181335},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.12262853980064392},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.05134320259094238},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.04965829849243164}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4304/jcp.9.6.1316-1324","is_oa":false,"landing_page_url":"https://doi.org/10.4304/jcp.9.6.1316-1324","pdf_url":null,"source":{"id":"https://openalex.org/S77894049","display_name":"Journal of Computers","issn_l":"1796-203X","issn":["1796-203X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318660","host_organization_name":"Academy Publisher","host_organization_lineage":["https://openalex.org/P4310318660"],"host_organization_lineage_names":["Academy Publisher"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computers","raw_type":"journal-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.881.9086","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.881.9086","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ojs.academypublisher.com/index.php/jcp/article/download/jcp090613161324/9433/","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.49000000953674316}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1966900042","https://openalex.org/W1977224394","https://openalex.org/W1995875735","https://openalex.org/W1998663649","https://openalex.org/W2003850925","https://openalex.org/W2011029476","https://openalex.org/W2022059461","https://openalex.org/W2024910401","https://openalex.org/W2030417183","https://openalex.org/W2045727533","https://openalex.org/W2097110438","https://openalex.org/W2113065518","https://openalex.org/W2140360868","https://openalex.org/W2152322845","https://openalex.org/W2161494102","https://openalex.org/W2171168067","https://openalex.org/W2178319414","https://openalex.org/W2185599799","https://openalex.org/W2311485094","https://openalex.org/W2313866064","https://openalex.org/W2322688780","https://openalex.org/W2327328448","https://openalex.org/W2348410644","https://openalex.org/W2349349154","https://openalex.org/W2349886474","https://openalex.org/W2365382545","https://openalex.org/W2371226194","https://openalex.org/W2373766213","https://openalex.org/W2375757435","https://openalex.org/W2385367983","https://openalex.org/W2389406890","https://openalex.org/W2391391664","https://openalex.org/W2992123465","https://openalex.org/W3002608735","https://openalex.org/W4255833381","https://openalex.org/W4285719527","https://openalex.org/W6641712146","https://openalex.org/W6682541512","https://openalex.org/W6990322636","https://openalex.org/W7026791766"],"related_works":["https://openalex.org/W2607400777","https://openalex.org/W3165971014","https://openalex.org/W2745001864","https://openalex.org/W2626924204","https://openalex.org/W1457719682","https://openalex.org/W2391601053","https://openalex.org/W2139206670","https://openalex.org/W2532531558","https://openalex.org/W4246510521","https://openalex.org/W2728991141"],"abstract_inverted_index":{"Abstract\u2014Traditional":[0],"rough":[1,17,40,164],"set":[2,88],"theory":[3],"is":[4,47,89,137,150],"only":[5],"suitable":[6],"for":[7],"dealing":[8],"with":[9,22,49],"discrete":[10],"variables":[11],"and":[12,102,144,152],"need":[13],"data":[14,118,130],"preprocessing.":[15],"Neighborhood":[16],"sets":[18],"overcome":[19],"these":[20,70],"shortcomings":[21],"the":[23,33,44,54,61,66,73,76,80,85,109,115,122,128,157],"ability":[24],"to":[25,52,98,120,127,139,156],"directly":[26],"process":[27],"numeric":[28],"data.":[29,161],"This":[30],"paper":[31],"modifies":[32],"attribute":[34,45,74,87,95,168],"reduction":[35,81,96],"method":[36,97],"based":[37],"on":[38],"neighborhood":[39],"sets,":[41,165],"in":[42,159],"which":[43],"importance":[46,63],"combined":[48],"information":[50,67,166],"entropy":[51,68,78],"select":[53],"appropriate":[55],"attributes.":[56,71],"When":[57],"multiple":[58],"attributes":[59],"have":[60],"same":[62],"degree,":[64],"compare":[65],"of":[69,117],"Put":[72],"having":[75],"minimal":[77],"into":[79],"set,":[82],"so":[83],"that":[84],"reduced":[86],"better.":[90],"Then":[91],"we":[92],"introduce":[93],"this":[94],"improve":[99],"spectral":[100,141,170],"clustering":[101,124,142,148,171],"propose":[103],"NRSR-SC":[104,135],"algorithm.":[105,146],"It":[106],"can":[107],"highlight":[108],"differences":[110],"between":[111],"samples":[112],"while":[113],"maintaining":[114],"characteristics":[116],"points":[119],"make":[121],"final":[123],"results":[125],"closer":[126],"real":[129],"classes.":[131],"Experiments":[132],"show":[133],"that,":[134],"algorithm":[136,143],"superior":[138],"traditional":[140],"FCM":[145],"Its":[147],"accuracy":[149],"higher,":[151],"has":[153],"strong":[154],"robustness":[155],"noise":[158],"high-dimensional":[160],"Index":[162],"Terms\u2014neighborhood":[163],"entropy,":[167],"reduction,":[169],"I.":[172]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":5},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}