{"id":"https://openalex.org/W2922190441","doi":"https://doi.org/10.23919/apsipa.2018.8659506","title":"Measuring Researcher Relatedness with Changes in Their Research Interests","display_name":"Measuring Researcher Relatedness with Changes in Their Research Interests","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2922190441","doi":"https://doi.org/10.23919/apsipa.2018.8659506","mag":"2922190441"},"language":"en","primary_location":{"id":"doi:10.23919/apsipa.2018.8659506","is_oa":false,"landing_page_url":"https://doi.org/10.23919/apsipa.2018.8659506","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5039257087","display_name":"Hiroyuki Nishizawa","orcid":null},"institutions":[{"id":"https://openalex.org/I133984924","display_name":"Doshisha University","ror":"https://ror.org/01fxdkm29","country_code":"JP","type":"education","lineage":["https://openalex.org/I133984924"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Hiroyuki Nishizawa","raw_affiliation_strings":["Doshisha University, Kyoto, Japan"],"affiliations":[{"raw_affiliation_string":"Doshisha University, Kyoto, Japan","institution_ids":["https://openalex.org/I133984924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040938369","display_name":"Marie Katsurai","orcid":"https://orcid.org/0000-0003-4899-2427"},"institutions":[{"id":"https://openalex.org/I133984924","display_name":"Doshisha University","ror":"https://ror.org/01fxdkm29","country_code":"JP","type":"education","lineage":["https://openalex.org/I133984924"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Marie Katsurai","raw_affiliation_strings":["Doshisha University, Kyoto, Japan"],"affiliations":[{"raw_affiliation_string":"Doshisha University, Kyoto, Japan","institution_ids":["https://openalex.org/I133984924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083291634","display_name":"Ikki Ohmukai","orcid":"https://orcid.org/0000-0002-3276-3753"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ikki Ohmukai","raw_affiliation_strings":["National Institute of Informatics, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Informatics, Tokyo, Japan","institution_ids":["https://openalex.org/I184597095"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043917711","display_name":"Hideaki Takeda","orcid":"https://orcid.org/0000-0002-2909-7163"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hideaki Takeda","raw_affiliation_strings":["National Institute of Informatics, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Informatics, Tokyo, Japan","institution_ids":["https://openalex.org/I184597095"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5039257087"],"corresponding_institution_ids":["https://openalex.org/I133984924"],"apc_list":null,"apc_paid":null,"fwci":0.7854,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.82606697,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"149","last_page":"152"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13274","display_name":"Expert finding and Q&A systems","score":0.9973000288009644,"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"}},"topics":[{"id":"https://openalex.org/T13274","display_name":"Expert finding and Q&A systems","score":0.9973000288009644,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9965999722480774,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.7228307127952576},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7150387763977051},{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"Dynamic time warping","score":0.624650239944458},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6233553886413574},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5969967842102051},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5910325646400452},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5043493509292603},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.4456174075603485},{"id":"https://openalex.org/keywords/similarity-measure","display_name":"Similarity measure","score":0.441057413816452},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.31517377495765686},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26381275057792664},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09379440546035767}],"concepts":[{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7228307127952576},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7150387763977051},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.624650239944458},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6233553886413574},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5969967842102051},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5910325646400452},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5043493509292603},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.4456174075603485},{"id":"https://openalex.org/C2776517306","wikidata":"https://www.wikidata.org/wiki/Q29017317","display_name":"Similarity measure","level":2,"score":0.441057413816452},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31517377495765686},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26381275057792664},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09379440546035767},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/apsipa.2018.8659506","is_oa":false,"landing_page_url":"https://doi.org/10.23919/apsipa.2018.8659506","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W42768238","https://openalex.org/W116902681","https://openalex.org/W1644143874","https://openalex.org/W1880262756","https://openalex.org/W2007172042","https://openalex.org/W2015289818","https://openalex.org/W2053833676","https://openalex.org/W2059398827","https://openalex.org/W2094524282","https://openalex.org/W2122831750","https://openalex.org/W2127201730","https://openalex.org/W2288745370","https://openalex.org/W2326068566","https://openalex.org/W2601564074","https://openalex.org/W2613051960","https://openalex.org/W2743930630","https://openalex.org/W6604828220","https://openalex.org/W6636986036","https://openalex.org/W6639619044"],"related_works":["https://openalex.org/W2182136398","https://openalex.org/W2347413598","https://openalex.org/W2319693127","https://openalex.org/W308539617","https://openalex.org/W2032415964","https://openalex.org/W2014214435","https://openalex.org/W3049200503","https://openalex.org/W1983228818","https://openalex.org/W2591622283","https://openalex.org/W2052451333"],"abstract_inverted_index":{"Relevant":[0],"researcher":[1,15,27,108],"recommendation":[2,51],"is":[3],"important":[4],"for":[5],"finding":[6],"potential":[7],"research":[8,20],"collaborators,":[9],"and":[10,109],"several":[11],"existing":[12],"methods":[13],"measure":[14,80],"relatedness":[16,82],"based":[17],"on":[18,49],"their":[19],"interests.":[21],"Our":[22],"previous":[23],"works":[24],"represented":[25],"a":[26,29,68,106],"with":[28],"single":[30],"multidimensional":[31],"topic":[32,77,93,103,120],"vector":[33],"calculated":[34],"from":[35],"the":[36,40,44,54,81,87,112,129],"researcher's":[37],"publications,":[38],"ignoring":[39],"publication":[41],"dates.":[42],"On":[43],"other":[45],"hand,":[46],"recent":[47],"studies":[48],"information":[50],"have":[52],"shown":[53],"effectiveness":[55],"of":[56,71,75,92,105],"modeling":[57],"changes":[58],"in":[59],"user":[60],"preferences":[61],"over":[62,124],"time.":[63],"Thus,":[64],"this":[65],"paper":[66],"proposes":[67],"new":[69],"representation":[70],"researchers,":[72,84],"which":[73],"consists":[74],"yearly":[76],"vectors.":[78],"To":[79],"between":[83,89],"we":[85],"calculate":[86],"similarity":[88],"two":[90],"sequences":[91],"vectors":[94],"using":[95],"Dynamic":[96],"Time":[97],"Warping.":[98],"An":[99],"experimental":[100],"example":[101],"visualizes":[102],"transitions":[104,121],"target":[107],"demonstrates":[110],"that":[111],"proposed":[113],"method":[114],"can":[115],"effectively":[116],"find":[117],"researchers":[118],"whose":[119],"are":[122],"similar":[123],"time,":[125],"when":[126],"compared":[127],"to":[128],"conventional":[130],"method.":[131]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}