{"id":"https://openalex.org/W2065664933","doi":"https://doi.org/10.1145/2802083.2808402","title":"Fine-grained social relationship extraction from real activity data under coarse supervision","display_name":"Fine-grained social relationship extraction from real activity data under coarse supervision","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2065664933","doi":"https://doi.org/10.1145/2802083.2808402","mag":"2065664933"},"language":"en","primary_location":{"id":"doi:10.1145/2802083.2808402","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2802083.2808402","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2808402&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 ACM International Symposium on Wearable Computers - ISWC '15","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://dl.acm.org/ft_gateway.cfm?id=2808402&type=pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043621466","display_name":"Kota Tsubouchi","orcid":"https://orcid.org/0000-0002-7753-8939"},"institutions":[{"id":"https://openalex.org/I4210125947","display_name":"Japan Research Institute","ror":"https://ror.org/02m5srn05","country_code":"JP","type":"facility","lineage":["https://openalex.org/I4210125947"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Kota Tsubouchi","raw_affiliation_strings":["Yahoo! Japan Research, Tokyo, Japan","Yahoo! JAPAN Research, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"Yahoo! Japan Research, Tokyo, Japan","institution_ids":["https://openalex.org/I4210125947"]},{"raw_affiliation_string":"Yahoo! JAPAN Research, Tokyo, Japan","institution_ids":["https://openalex.org/I4210125947"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028050904","display_name":"Osamu Saisho","orcid":"https://orcid.org/0000-0002-8077-3251"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Osamu Saisho","raw_affiliation_strings":["The University of Tokyo, Tokyo, Japan","The University of Tokyo Tokyo Japan)"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"The University of Tokyo Tokyo Japan)","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111631347","display_name":"Junichi Sato","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Junichi Sato","raw_affiliation_strings":["The University of Tokyo, Tokyo, Japan","The University of Tokyo Tokyo Japan)"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"The University of Tokyo Tokyo Japan)","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078434556","display_name":"Seira Araki","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Seira Araki","raw_affiliation_strings":["The University of Tokyo, Tokyo, Japan","The University of Tokyo Tokyo Japan)"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"The University of Tokyo Tokyo Japan)","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032839697","display_name":"Masamichi Shimosaka","orcid":"https://orcid.org/0000-0003-0558-2006"},"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":"Masamichi Shimosaka","raw_affiliation_strings":["Tokyo Institute of Technology, Tokyo, Japan","[Tokyo Institute of Technology, Tokyo, JAPAN]"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Tokyo, Japan","institution_ids":["https://openalex.org/I114531698"]},{"raw_affiliation_string":"[Tokyo Institute of Technology, Tokyo, JAPAN]","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5043621466"],"corresponding_institution_ids":["https://openalex.org/I4210125947"],"apc_list":null,"apc_paid":null,"fwci":1.737,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.85090137,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"183","last_page":"187"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9977999925613403,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9977999925613403,"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"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11439","display_name":"Video Analysis and Summarization","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/extraction","display_name":"Extraction (chemistry)","score":0.6101787686347961},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6037703156471252},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.08189025521278381},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.06019583344459534}],"concepts":[{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.6101787686347961},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6037703156471252},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.08189025521278381},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.06019583344459534}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2802083.2808402","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2802083.2808402","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2808402&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 ACM International Symposium on Wearable Computers - ISWC '15","raw_type":"proceedings-article"},{"id":"pmh:oai:t2r2.star.titech.ac.jp:50504184","is_oa":false,"landing_page_url":"http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100812514","pdf_url":null,"source":{"id":"https://openalex.org/S4377196385","display_name":"Tokyo Tech Research Repository (Tokyo Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114531698","host_organization_name":"Tokyo Institute of Technology","host_organization_lineage":["https://openalex.org/I114531698"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":{"id":"doi:10.1145/2802083.2808402","is_oa":true,"landing_page_url":"https://doi.org/10.1145/2802083.2808402","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=2808402&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2015 ACM International Symposium on Wearable Computers - ISWC '15","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6100000143051147,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2065664933.pdf","grobid_xml":"https://content.openalex.org/works/W2065664933.grobid-xml"},"referenced_works_count":9,"referenced_works":["https://openalex.org/W77640178","https://openalex.org/W2088629124","https://openalex.org/W2108745803","https://openalex.org/W2110119381","https://openalex.org/W2123271629","https://openalex.org/W2126895033","https://openalex.org/W2130815877","https://openalex.org/W2131099807","https://openalex.org/W2166692930"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W2093578348","https://openalex.org/W2376932109","https://openalex.org/W2382290278","https://openalex.org/W2096946506","https://openalex.org/W2766271392","https://openalex.org/W2350741829"],"abstract_inverted_index":{"Understanding":[0],"social":[1,16,54,79,146],"relationships":[2,17,158],"plays":[3],"an":[4],"important":[5],"role":[6],"in":[7,60,127],"smooth":[8],"information":[9,103,121],"sharing":[10],"and":[11,25,74,107,112,141,153],"project":[12],"management.":[13],"Recently,":[14],"extracting":[15],"from":[18,82,159],"activity":[19,40],"sensor":[20,41,58],"data":[21,59,85,115,118],"has":[22],"gained":[23],"popularity,":[24],"many":[26],"researchers":[27],"have":[28],"tried":[29],"to":[30],"detect":[31],"close":[32],"relationship":[33,55,80,98,101],"pairs":[34],"based":[35,89],"on":[36,68,90],"the":[37,70,100,105,117,135,143],"similarities":[38],"between":[39],"data,":[42],"namely,":[43],"unsupervised":[44],"approaches.":[45],"However,":[46],"there":[47],"is":[48,116],"room":[49],"for":[50],"further":[51],"research":[52],"into":[53],"analysis":[56],"of":[57,62,72,137,156],"terms":[61],"extraction":[63,81,139,155],"performance.":[64],"We":[65],"therefore":[66],"focus":[67],"improving":[69],"accuracy":[71,152],"detection":[73,151],"propose":[75],"a":[76,128],"novel":[77],"fine-grained":[78,97,145,157],"coarse":[83,113,160],"supervision":[84,114,161],"by":[86],"supervised":[87],"approach":[88,149],"multiple":[91],"instance":[92],"learning.":[93],"In":[94,130],"this":[95,131],"paper,":[96],"means":[99],"including":[102],"about":[104,122],"time":[106],"duration":[108],"they":[109,124],"are":[110,125],"together,":[111],"containing":[119],"only":[120],"whether":[123],"together":[126],"day.":[129],"research,":[132],"we":[133],"evaluate":[134],"feasibility":[136],"our":[138],"method":[140],"analyze":[142],"extracted":[144],"relationships.":[147],"Our":[148],"improve":[150],"achieve":[154],"data.":[162]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
