{"id":"https://openalex.org/W2010123893","doi":"https://doi.org/10.1145/2095536.2095543","title":"Research history generation using maximum margin clustering of research papers based on metainformation","display_name":"Research history generation using maximum margin clustering of research papers based on metainformation","publication_year":2011,"publication_date":"2011-12-05","ids":{"openalex":"https://openalex.org/W2010123893","doi":"https://doi.org/10.1145/2095536.2095543","mag":"2010123893"},"language":"en","primary_location":{"id":"doi:10.1145/2095536.2095543","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2095536.2095543","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services","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/A5057715671","display_name":"Manh Cuong Nguyen","orcid":"https://orcid.org/0000-0002-6342-1393"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Manh Cuong Nguyen","raw_affiliation_strings":["Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103860365","display_name":"Daichi Kato","orcid":null},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Daichi Kato","raw_affiliation_strings":["Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022568434","display_name":"Haruo Yokota","orcid":"https://orcid.org/0000-0001-9788-0443"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Haruo Yokota","raw_affiliation_strings":["Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016165628","display_name":"Taiichi Hashimoto","orcid":null},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Taiichi Hashimoto","raw_affiliation_strings":["Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Ookayama, Meguro-ku, Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08714421,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"20","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9976000189781189,"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":0.9976000189781189,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9972000122070312,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9915000200271606,"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":0.8855412006378174},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6697412133216858},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6017519235610962},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5075727701187134},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5043100118637085},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4958280026912689},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.42641162872314453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39577189087867737},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3684449791908264},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33312177658081055},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.0532890260219574}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8855412006378174},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6697412133216858},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6017519235610962},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5075727701187134},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5043100118637085},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4958280026912689},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.42641162872314453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39577189087867737},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3684449791908264},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33312177658081055},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0532890260219574},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2095536.2095543","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2095536.2095543","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services","raw_type":"proceedings-article"},{"id":"pmh:oai:irdb.nii.ac.jp:00897:0004053134","is_oa":false,"landing_page_url":"http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100632214","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5927727034","display_name":null,"funder_award_id":"22240005","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":9,"referenced_works":["https://openalex.org/W146900863","https://openalex.org/W155032588","https://openalex.org/W2029088861","https://openalex.org/W2132820034","https://openalex.org/W2136518509","https://openalex.org/W2148603752","https://openalex.org/W2149982386","https://openalex.org/W2166765763","https://openalex.org/W2595697910"],"related_works":["https://openalex.org/W2379140333","https://openalex.org/W1999117613","https://openalex.org/W2040929534","https://openalex.org/W3022637481","https://openalex.org/W2393816671","https://openalex.org/W3120229345","https://openalex.org/W2804957450","https://openalex.org/W3144143113","https://openalex.org/W3039964395","https://openalex.org/W2111119584"],"abstract_inverted_index":{"Our":[0],"research":[1,10,13],"aim":[2],"is":[3,41,54,66,70,117,123,128],"the":[4,17,24,35,38,109],"automatic":[5],"generation":[6,21],"of":[7,37,111],"a":[8,45,55,112],"researcher's":[9],"history":[11,20],"from":[12],"articles":[14,87],"published":[15],"on":[16,23,48,60,115],"internet.":[18],"Research":[19],"based":[22,47,59,114],"k-Means":[25,39],"clustering":[26,57,74],"algorithm":[27,40,58],"has":[28],"been":[29],"proposed":[30],"in":[31,133],"previous":[32,134],"work.":[33],"However,":[34],"performance":[36],"unsatisfactory.":[42],"We":[43,104],"propose":[44],"method":[46,113],"Maximum":[49],"Margin":[50],"Clustering":[51],"(MMC).":[52],"MMC":[53,69,102,116],"new":[56],"Support":[61],"Vector":[62],"Machines":[63],"(SVM).":[64],"It":[65],"known":[67],"that":[68,108,131],"better":[71,129],"than":[72,130],"existing":[73],"algorithms":[75],"such":[76],"as":[77],"k-Means.":[78],"In":[79],"this":[80],"paper,":[81],"we":[82],"describe":[83],"how":[84,95],"to":[85,96],"convert":[86],"into":[88],"vectors":[89],"using":[90],"metainformation":[91],"about":[92,118,124],"them":[93],"and":[94,120],"decide":[97],"an":[98],"initial":[99],"setting":[100],"for":[101],"automatically.":[103],"demonstrate":[105],"by":[106],"experiment":[107],"purity":[110],"0.58":[119],"its":[121],"entropy":[122],"0.415.":[125],"This":[126],"result":[127],"achieved":[132],"work":[135],"(purity:":[136],"0.35,":[137],"entropy:":[138],"0.47).":[139]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}