{"id":"https://openalex.org/W2139019776","doi":"https://doi.org/10.1109/icdm.2003.1250938","title":"Visualization of rule's similarity using multidimensional scaling","display_name":"Visualization of rule's similarity using multidimensional scaling","publication_year":2004,"publication_date":"2004-04-23","ids":{"openalex":"https://openalex.org/W2139019776","doi":"https://doi.org/10.1109/icdm.2003.1250938","mag":"2139019776"},"language":"en","primary_location":{"id":"doi:10.1109/icdm.2003.1250938","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2003.1250938","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Third IEEE International Conference on Data Mining","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/A5006566635","display_name":"Shusaku Tsumoto","orcid":"https://orcid.org/0000-0001-6651-976X"},"institutions":[{"id":"https://openalex.org/I169016828","display_name":"Shimane University","ror":"https://ror.org/01jaaym28","country_code":"JP","type":"education","lineage":["https://openalex.org/I169016828"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"S. Tsumoto","raw_affiliation_strings":["Department of Medical Informatics, School of Medicine, Shimane University, Izumo, Shimane, Japan","Dept. of Med. Informatics, Shimane Univ., Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Medical Informatics, School of Medicine, Shimane University, Izumo, Shimane, Japan","institution_ids":["https://openalex.org/I169016828"]},{"raw_affiliation_string":"Dept. of Med. Informatics, Shimane Univ., Japan","institution_ids":["https://openalex.org/I169016828"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100974031","display_name":"S. Hirano","orcid":null},"institutions":[{"id":"https://openalex.org/I169016828","display_name":"Shimane University","ror":"https://ror.org/01jaaym28","country_code":"JP","type":"education","lineage":["https://openalex.org/I169016828"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"S. Hirano","raw_affiliation_strings":["Department of Medical Informatics, School of Medicine, Shimane University, Izumo, Shimane, Japan","Dept. of Med. Informatics, Shimane Univ., Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Medical Informatics, School of Medicine, Shimane University, Izumo, Shimane, Japan","institution_ids":["https://openalex.org/I169016828"]},{"raw_affiliation_string":"Dept. of Med. Informatics, Shimane Univ., Japan","institution_ids":["https://openalex.org/I169016828"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.8073,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.93506144,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"339","last_page":"346"},"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9991000294685364,"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"}},{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/computer-science","display_name":"Computer science","score":0.7034147381782532},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6470863819122314},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6347193717956543},{"id":"https://openalex.org/keywords/knowledge-extraction","display_name":"Knowledge extraction","score":0.6215738654136658},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6202307939529419},{"id":"https://openalex.org/keywords/multidimensional-scaling","display_name":"Multidimensional scaling","score":0.5982571840286255},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5476107597351074},{"id":"https://openalex.org/keywords/rule-induction","display_name":"Rule induction","score":0.46822234988212585},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.45253971219062805},{"id":"https://openalex.org/keywords/data-visualization","display_name":"Data visualization","score":0.4443090558052063},{"id":"https://openalex.org/keywords/rule-based-system","display_name":"Rule-based system","score":0.4117482602596283},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30180397629737854},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22299280762672424},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16345444321632385},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10309231281280518}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7034147381782532},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6470863819122314},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6347193717956543},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.6215738654136658},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6202307939529419},{"id":"https://openalex.org/C91682802","wikidata":"https://www.wikidata.org/wiki/Q620538","display_name":"Multidimensional scaling","level":2,"score":0.5982571840286255},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5476107597351074},{"id":"https://openalex.org/C2776780472","wikidata":"https://www.wikidata.org/wiki/Q7378945","display_name":"Rule induction","level":2,"score":0.46822234988212585},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.45253971219062805},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.4443090558052063},{"id":"https://openalex.org/C149271511","wikidata":"https://www.wikidata.org/wiki/Q1417149","display_name":"Rule-based system","level":2,"score":0.4117482602596283},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30180397629737854},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22299280762672424},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16345444321632385},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10309231281280518},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icdm.2003.1250938","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icdm.2003.1250938","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Third IEEE International Conference on Data Mining","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":13,"referenced_works":["https://openalex.org/W1592094058","https://openalex.org/W1992107931","https://openalex.org/W2004026774","https://openalex.org/W2033626294","https://openalex.org/W2081550846","https://openalex.org/W2323746689","https://openalex.org/W2340020088","https://openalex.org/W2479500547","https://openalex.org/W2612166593","https://openalex.org/W4232953319","https://openalex.org/W4250426676","https://openalex.org/W4252259391","https://openalex.org/W6635379975"],"related_works":["https://openalex.org/W2357854711","https://openalex.org/W4243448361","https://openalex.org/W1813387235","https://openalex.org/W2051700896","https://openalex.org/W1552255772","https://openalex.org/W2111524952","https://openalex.org/W2054759342","https://openalex.org/W4234690372","https://openalex.org/W1975947159","https://openalex.org/W4239551281"],"abstract_inverted_index":{"One":[0],"of":[1,22,99],"the":[2,46,73,87,97,108,128],"most":[3],"important":[4],"problems":[5],"with":[6,78],"rule":[7,66,75],"induction":[8],"methods":[9],"is":[10,13],"that":[11,151],"it":[12],"very":[14],"difficult":[15],"for":[16,154],"domain":[17,37,155],"experts":[18,156],"to":[19,81,96,106,123],"check":[20],"millions":[21],"rules":[23,32,62,91,112],"generated":[24],"from":[25,30,36,127],"large":[26],"datasets.":[27],"The":[28],"discovery":[29,98],"these":[31,54,90],"requires":[33],"deep":[34],"interpretation":[35],"knowledge.":[38,100],"Although":[39],"several":[40],"solutions":[41],"have":[42],"been":[43],"proposed":[44],"in":[45],"studies":[47,55],"on":[48,59,114,142],"data":[49,125,134,145],"mining":[50],"and":[51,72,135],"knowledge":[52,152],"discovery,":[53],"are":[56],"not":[57],"focused":[58],"similarities":[60,131],"between":[61,89,111,132],"obtained.":[63],"When":[64],"one":[65],"r/sub":[67,76,82],"1/":[68,83],"has":[69],"reasonable":[70],"features":[71],"other":[74],"2/":[77],"high":[79],"similarity":[80],"includes":[84],"unexpected":[85],"factors,":[86],"relations":[88,110],"will":[92],"become":[93],"a":[94,103,119],"trigger":[95],"We":[101,138],"propose":[102],"visualization":[104],"approach":[105],"show":[107,150],"similar":[109],"based":[113],"multidimensional":[115],"scaling,":[116],"which":[117],"assign":[118],"two-dimensional":[120],"cartesian":[121],"coordinate":[122],"each":[124],"point":[126],"information":[129],"about":[130],"this":[133,140],"others":[136],"data.":[137],"evaluated":[139],"method":[141],"two":[143],"medical":[144],"sets,":[146],"whose":[147],"experimental":[148],"results":[149],"useful":[153],"could":[157],"be":[158],"found.":[159]},"counts_by_year":[{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}