{"id":"https://openalex.org/W2765320439","doi":"https://doi.org/10.1002/pra2.2017.14505401182","title":"Research collaboration prediction and recommendation based on network embedding in co\u2010authorship networks","display_name":"Research collaboration prediction and recommendation based on network embedding in co\u2010authorship networks","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2765320439","doi":"https://doi.org/10.1002/pra2.2017.14505401182","mag":"2765320439"},"language":"en","primary_location":{"id":"doi:10.1002/pra2.2017.14505401182","is_oa":false,"landing_page_url":"https://doi.org/10.1002/pra2.2017.14505401182","pdf_url":null,"source":{"id":"https://openalex.org/S4393918545","display_name":"Proceedings of the Association for Information Science and Technology","issn_l":"2373-9231","issn":["2373-9231"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Association for Information Science and Technology","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/A5102966742","display_name":"Jinzhu Zhang","orcid":"https://orcid.org/0000-0001-7581-1850"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jinzhu Zhang","raw_affiliation_strings":["Department of Information Management Nanjing University of Science and Technology  China","Department of Information Management, Nanjing University of Science and Technology, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Management Nanjing University of Science and Technology  China","institution_ids":["https://openalex.org/I36399199"]},{"raw_affiliation_string":"Department of Information Management, Nanjing University of Science and Technology, China","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5102966742"],"corresponding_institution_ids":["https://openalex.org/I36399199"],"apc_list":null,"apc_paid":null,"fwci":0.2081,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.65318807,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"54","issue":"1","first_page":"847","last_page":"849"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9990000128746033,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9990000128746033,"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":0.995199978351593,"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"}},{"id":"https://openalex.org/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.9865000247955322,"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/computer-science","display_name":"Computer science","score":0.7244236469268799},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6728898882865906},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6541943550109863},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.5963718295097351},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5622466802597046},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5489996075630188},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5249086618423462},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5048104524612427},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43625330924987793},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4164174497127533},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3958471417427063},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3317021429538727},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10181534290313721}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7244236469268799},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6728898882865906},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6541943550109863},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.5963718295097351},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5622466802597046},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5489996075630188},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5249086618423462},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5048104524612427},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43625330924987793},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4164174497127533},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3958471417427063},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3317021429538727},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10181534290313721},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/pra2.2017.14505401182","is_oa":false,"landing_page_url":"https://doi.org/10.1002/pra2.2017.14505401182","pdf_url":null,"source":{"id":"https://openalex.org/S4393918545","display_name":"Proceedings of the Association for Information Science and Technology","issn_l":"2373-9231","issn":["2373-9231"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Association for Information Science and Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1528370171","https://openalex.org/W1859627028","https://openalex.org/W1888005072","https://openalex.org/W1979104937","https://openalex.org/W2005375780","https://openalex.org/W2101900104","https://openalex.org/W2124054611","https://openalex.org/W2137793309","https://openalex.org/W2154851992","https://openalex.org/W2257646213","https://openalex.org/W2469190938","https://openalex.org/W3098818882","https://openalex.org/W3104097132","https://openalex.org/W3105705953"],"related_works":["https://openalex.org/W2380556669","https://openalex.org/W2396424089","https://openalex.org/W2373031548","https://openalex.org/W2605245466","https://openalex.org/W2373229007","https://openalex.org/W2158017000","https://openalex.org/W2506594442","https://openalex.org/W2146960954","https://openalex.org/W4239349090","https://openalex.org/W2596026555"],"abstract_inverted_index":{"ABSTRACT":[0],"In":[1],"large\u2010scale":[2,62],"datasets,":[3],"the":[4,21,34,40,47,55,72,77,82,99,118,128,132],"researchers'":[5,73],"multiple":[6],"features":[7],"need":[8],"to":[9,19,38],"be":[10],"learned":[11,80],"automatically":[12],"instead":[13],"of":[14,25,42,120,136],"manually":[15],"defined":[16],"and":[17,23,29,90,110,122,134,140],"enumerated,":[18],"improve":[20,131],"efficiency":[22],"effect":[24],"research":[26,65,137],"collaboration":[27,138],"prediction":[28,139],"recommendation.":[30,141],"This":[31],"paper":[32],"applies":[33],"network":[35,57,78,83],"embedding":[36,84],"method":[37,85,129],"learn":[39],"context":[41],"each":[43,91],"researcher":[44],"by":[45,69,81,113],"which":[46],"semantic":[48,74,100],"similarities":[49,101],"among":[50,102],"researchers":[51,103],"are":[52,67,79,104],"calculated.":[53],"Firstly,":[54],"co\u2010authorship":[56],"is":[58,96],"built":[59],"in":[60,76,117],"a":[61],"dataset":[63],"where":[64],"collaborations":[66],"denoted":[68],"co\u2010authorships.":[70],"Then":[71],"contexts":[75],"based":[86],"on":[87],"deep":[88],"learning,":[89],"researcher's":[92],"dense,":[93],"low\u2010dimensional":[94],"vector":[95,107],"formed.":[97],"Finally,":[98],"calculated":[105],"through":[106],"similarity":[108],"indices":[109],"quantitatively":[111],"compared":[112],"link":[114],"prediction.":[115],"Experiments":[116],"field":[119],"library":[121],"information":[123],"science":[124],"(LIS)":[125],"verify":[126],"that":[127],"can":[130],"accuracy":[133],"effectiveness":[135]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}