{"id":"https://openalex.org/W2992271252","doi":"https://doi.org/10.1109/icawst.2019.8923316","title":"Productivity-based Features from Article Metadata for Fuzzy Rules to Classify Academic Expert","display_name":"Productivity-based Features from Article Metadata for Fuzzy Rules to Classify Academic Expert","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2992271252","doi":"https://doi.org/10.1109/icawst.2019.8923316","mag":"2992271252"},"language":"en","primary_location":{"id":"doi:10.1109/icawst.2019.8923316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icawst.2019.8923316","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST)","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/A5055527258","display_name":"Diana Purwitasari","orcid":"https://orcid.org/0000-0001-7000-7628"},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":true,"raw_author_name":"Diana Purwitasari","raw_affiliation_strings":["Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065837975","display_name":"Chastine Fatichah","orcid":"https://orcid.org/0000-0002-7348-9762"},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Chastine Fatichah","raw_affiliation_strings":["Department of Informatics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia"],"affiliations":[{"raw_affiliation_string":"Department of Informatics, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054122289","display_name":"Adri Gabriel Sooai","orcid":"https://orcid.org/0000-0001-5653-0420"},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Adri Gabriel Sooai","raw_affiliation_strings":["Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019052119","display_name":"Surya Sumpeno","orcid":"https://orcid.org/0000-0002-1744-1342"},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Surya Sumpeno","raw_affiliation_strings":["Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","institution_ids":["https://openalex.org/I166843116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012595591","display_name":"Mauridhi Hery Purnomo","orcid":"https://orcid.org/0000-0002-6221-7382"},"institutions":[{"id":"https://openalex.org/I166843116","display_name":"Sepuluh Nopember Institute of Technology","ror":"https://ror.org/05kbmmt89","country_code":"ID","type":"education","lineage":["https://openalex.org/I166843116"]}],"countries":["ID"],"is_corresponding":false,"raw_author_name":"Mauridhi Hery Purnomo","raw_affiliation_strings":["Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia","institution_ids":["https://openalex.org/I166843116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5055527258"],"corresponding_institution_ids":["https://openalex.org/I166843116"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.22817085,"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":"1","last_page":"6"},"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":1.0,"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":1.0,"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/T10028","display_name":"Topic Modeling","score":0.9936000108718872,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9659000039100647,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7859357595443726},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.6757606267929077},{"id":"https://openalex.org/keywords/productivity","display_name":"Productivity","score":0.6661354303359985},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5770857334136963},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.5750830769538879},{"id":"https://openalex.org/keywords/expert-system","display_name":"Expert system","score":0.5584803223609924},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5378723740577698},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.48957762122154236},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47594261169433594},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45008817315101624},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.42020317912101746},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4142988920211792},{"id":"https://openalex.org/keywords/knowledge-management","display_name":"Knowledge management","score":0.34621745347976685},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.13585764169692993},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0788673460483551}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7859357595443726},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.6757606267929077},{"id":"https://openalex.org/C204983608","wikidata":"https://www.wikidata.org/wiki/Q2111958","display_name":"Productivity","level":2,"score":0.6661354303359985},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5770857334136963},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.5750830769538879},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.5584803223609924},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5378723740577698},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.48957762122154236},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47594261169433594},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45008817315101624},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.42020317912101746},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4142988920211792},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.34621745347976685},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.13585764169692993},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0788673460483551},{"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/C139719470","wikidata":"https://www.wikidata.org/wiki/Q39680","display_name":"Macroeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icawst.2019.8923316","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icawst.2019.8923316","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 10th International Conference on Awareness Science and Technology (iCAST)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1779897838","https://openalex.org/W1993880406","https://openalex.org/W2041987923","https://openalex.org/W2053380178","https://openalex.org/W2077806522","https://openalex.org/W2101234009","https://openalex.org/W2119798704","https://openalex.org/W2153579005","https://openalex.org/W2166686248","https://openalex.org/W2178628967","https://openalex.org/W2187089797","https://openalex.org/W2272453175","https://openalex.org/W2396496669","https://openalex.org/W2570749949","https://openalex.org/W2751018680","https://openalex.org/W2774749321","https://openalex.org/W2798942136","https://openalex.org/W2899016443","https://openalex.org/W2920503532","https://openalex.org/W2939250612","https://openalex.org/W4294170691","https://openalex.org/W6675354045","https://openalex.org/W6678003628","https://openalex.org/W6682691769"],"related_works":["https://openalex.org/W2392768766","https://openalex.org/W2058118494","https://openalex.org/W2382021449","https://openalex.org/W2095118173","https://openalex.org/W2104269053","https://openalex.org/W2106424170","https://openalex.org/W1985426483","https://openalex.org/W2501188010","https://openalex.org/W4299935056","https://openalex.org/W2010935248"],"abstract_inverted_index":{"Since":[0],"modeling":[1],"expertise":[2,18,48,61,73,121,127,138,164],"is":[3,75],"necessary":[4],"in":[5,19,77,97,108],"an":[6,34],"expert":[7,69,79,110],"recommendation":[8,111],"system,":[9],"this":[10],"paper":[11,83],"addressed":[12],"the":[13,20,55,59,68,72,78,89,98,109,114,144,155,174,186],"issue":[14],"to":[15,53,87,131,140],"obtain":[16],"researcher":[17],"academic":[21],"field":[22],"on":[23,63,85,154,193],"certain":[24,64],"topic":[25,65,195],"interest.":[26,196],"The":[27,36],"profile":[28],"considers":[29],"productivity":[30,37,94],"and":[31,95,125,149],"dynamicity":[32,56,96],"of":[33,38,93,100,117,136,146,188],"expert.":[35],"research":[39,45],"activities":[40],"through":[41],"published":[42],"articles":[43],"as":[44],"output":[46],"determine":[47],"that":[49],"changes":[50],"over":[51],"time":[52],"indicate":[54],"aspect.":[57],"Here,":[58],"resulted":[60],"status":[62,74,90,128,187],"interest":[66],"augments":[67],"profile.":[70],"However,":[71],"unavailable":[76,137],"finder":[80],"dataset.":[81],"This":[82],"discussed":[84],"approaches":[86,115],"classify":[88],"from":[91,160,166],"features":[92,180],"form":[99],"fuzzy":[101,133,167],"rules,":[102,175],"which":[103],"can":[104],"be":[105],"applied":[106],"later":[107],"system.":[112],"Then,":[113],"include":[116],"determining":[118],"topics,":[119],"mapping":[120],"candidates,":[122],"extracting":[123],"features,":[124],"labeling":[126],"for":[129,184],"training":[130],"generate":[132],"rules.":[134],"Because":[135],"status,":[139],"get":[141],"better":[142,170],"labels,":[143],"results":[145],"linear":[147],"model":[148],"clustering":[150,168],"were":[151,181],"compared.":[152],"Based":[153],"empirical":[156],"experiments,":[157],"rules":[158],"trained":[159],"scaled":[161],"data":[162],"with":[163,178],"labels":[165],"gave":[169],"results.":[171],"After":[172],"simplifying":[173],"if-then":[176],"forms":[177],"two":[179],"representable":[182],"enough":[183],"identifying":[185],"specialist":[189],"or":[190],"thriving":[191],"experts":[192],"a":[194]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
