{"id":"https://openalex.org/W2333920286","doi":"https://doi.org/10.3233/idt-150252","title":"Matrix-like visualization based on topic modeling for discovering connections between disjoint disciplines","display_name":"Matrix-like visualization based on topic modeling for discovering connections between disjoint disciplines","publication_year":2016,"publication_date":"2016-06-15","ids":{"openalex":"https://openalex.org/W2333920286","doi":"https://doi.org/10.3233/idt-150252","mag":"2333920286"},"language":"en","primary_location":{"id":"doi:10.3233/idt-150252","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-150252","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Decision Technologies","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/A5101423798","display_name":"Ji Qi","orcid":"https://orcid.org/0009-0002-8829-309X"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ji Qi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5060604714","display_name":"Yukio Ohsawa","orcid":"https://orcid.org/0000-0003-2943-2547"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yukio Ohsawa","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5101423798"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.196,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.79576268,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"10","issue":"3","first_page":"273","last_page":"283"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10215","display_name":"Semantic Web and Ontologies","score":0.9968000054359436,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.8096123933792114},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7739646434783936},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5875470042228699},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5173072814941406},{"id":"https://openalex.org/keywords/biclustering","display_name":"Biclustering","score":0.5139486193656921},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5018494129180908},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.47554919123649597},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.45227864384651184},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.45164889097213745},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.41779381036758423},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3782798647880554},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33500978350639343},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32244452834129333},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.23748821020126343}],"concepts":[{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.8096123933792114},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7739646434783936},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5875470042228699},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5173072814941406},{"id":"https://openalex.org/C144817290","wikidata":"https://www.wikidata.org/wiki/Q2976575","display_name":"Biclustering","level":5,"score":0.5139486193656921},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5018494129180908},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.47554919123649597},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.45227864384651184},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.45164889097213745},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.41779381036758423},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3782798647880554},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33500978350639343},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32244452834129333},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.23748821020126343},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.0},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/idt-150252","is_oa":false,"landing_page_url":"https://doi.org/10.3233/idt-150252","pdf_url":null,"source":{"id":"https://openalex.org/S119727669","display_name":"Intelligent Decision Technologies","issn_l":"1872-4981","issn":["1872-4981","1875-8843"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Decision Technologies","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8700000047683716,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1493217831","https://openalex.org/W1667925084","https://openalex.org/W1976909068","https://openalex.org/W1979406869","https://openalex.org/W2011726136","https://openalex.org/W2015954361","https://openalex.org/W2024030746","https://openalex.org/W2038316408","https://openalex.org/W2061572799","https://openalex.org/W2069366497","https://openalex.org/W2079639311","https://openalex.org/W2105562985","https://openalex.org/W2118229453","https://openalex.org/W2130190939","https://openalex.org/W2143525943","https://openalex.org/W2145074288","https://openalex.org/W2150930396","https://openalex.org/W4239389735","https://openalex.org/W4253608092","https://openalex.org/W6629329278"],"related_works":["https://openalex.org/W1974340769","https://openalex.org/W2900595096","https://openalex.org/W4289277241","https://openalex.org/W2979322793","https://openalex.org/W2765801824","https://openalex.org/W2188068678","https://openalex.org/W2157302779","https://openalex.org/W4236723217","https://openalex.org/W4226363062","https://openalex.org/W2592285132"],"abstract_inverted_index":{"Interdisciplinary":[0],"research":[1],"is":[2],"challenging":[3],"because":[4],"of":[5,28,51,64,67],"the":[6,26,60,65,68,102,120,138],"knowledge":[7,151],"overspecialization":[8],"problem,":[9],"which":[10,108],"makes":[11],"it":[12,42],"difficult":[13],"for":[14,83],"researchers":[15],"to":[16,96,133,152],"discover":[17],"connections":[18,85,95,154],"between":[19,86,155],"disjoint":[20,87,112],"disciplines.":[21,88,113,156],"Closed":[22],"Literature-based":[23],"discovery":[24],"shows":[25],"potentials":[27],"solving":[29],"this":[30,71,116],"problem":[31],"by":[32,100,124],"using":[33],"information":[34],"retrieval":[35],"and":[36,62,127],"natural":[37],"language":[38],"processing":[39],"techniques.":[40],"However,":[41],"still":[43],"faces":[44],"some":[45],"drawbacks,":[46],"such":[47],"as":[48],"large":[49],"amounts":[50],"manual":[52],"works":[53],"with":[54],"prior":[55,150],"knowledge,":[56],"difficulty":[57],"in":[58,137],"understanding":[59],"discoveries,":[61],"limitation":[63],"extension":[66],"domain.":[69],"In":[70],"paper,":[72],"we":[73,92,104,118],"propose":[74],"a":[75],"matrix-like":[76],"visualization":[77],"approach":[78,145],"based":[79],"on":[80],"topic":[81,125],"modeling":[82,126],"discovering":[84],"With":[89],"our":[90,144],"approach,":[91],"expect":[93],"interdisciplinary":[94],"be":[97],"efficiently":[98],"discovered":[99],"detecting":[101],"topics":[103,136],"call":[105],"mixed":[106,135],"topics,":[107],"contain":[109],"literature":[110],"from":[111],"For":[114],"achieving":[115],"purpose,":[117],"visualize":[119],"document-phrase":[121],"matrix":[122],"generated":[123],"develop":[128],"an":[129],"original":[130],"biclustering":[131],"algorithm":[132],"extract":[134],"matrix.":[139],"Experiment":[140],"results":[141],"show":[142],"that":[143],"can":[146],"help":[147],"users":[148],"without":[149],"detect":[153]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":1}],"updated_date":"2026-06-23T06:36:01.041984","created_date":"2025-10-10T00:00:00"}
