{"id":"https://openalex.org/W3021118808","doi":"https://doi.org/10.1108/ijwis-10-2019-0048","title":"RDF graph mining for cluster-based theme identification","display_name":"RDF graph mining for cluster-based theme identification","publication_year":2020,"publication_date":"2020-04-17","ids":{"openalex":"https://openalex.org/W3021118808","doi":"https://doi.org/10.1108/ijwis-10-2019-0048","mag":"3021118808"},"language":"en","primary_location":{"id":"doi:10.1108/ijwis-10-2019-0048","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ijwis-10-2019-0048","pdf_url":null,"source":{"id":"https://openalex.org/S145159096","display_name":"International Journal of Web Information Systems","issn_l":"1744-0084","issn":["1744-0084","1744-0092"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Web Information Systems","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/A5068905049","display_name":"Siham Eddamiri","orcid":"https://orcid.org/0000-0001-8257-1664"},"institutions":[{"id":"https://openalex.org/I4210153608","display_name":"Universit\u00e9 Moulay Ismail de Meknes","ror":"https://ror.org/04cnscd67","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210153608"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Siham Eddamiri","raw_affiliation_strings":["Department of Mathematics and Computer Science, University Moulay Ismail, ENSAM, Meknes, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, University Moulay Ismail, ENSAM, Meknes, Morocco","institution_ids":["https://openalex.org/I4210153608"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026677528","display_name":"Asmaa Benghabrit","orcid":"https://orcid.org/0000-0003-4330-439X"},"institutions":[{"id":"https://openalex.org/I126477371","display_name":"Mohammed V University","ror":"https://ror.org/00r8w8f84","country_code":"MA","type":"education","lineage":["https://openalex.org/I126477371"]},{"id":"https://openalex.org/I127336678","display_name":"Ecole Mohammadia d'Ing\u00e9nieurs","ror":"https://ror.org/00md3qm14","country_code":"MA","type":"education","lineage":["https://openalex.org/I127336678"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Asmaa Benghabrit","raw_affiliation_strings":["LMAID Laboratory, Universite Mohammed V de Rabat Ecole Mohammadia d'Ingenieurs, Rabat, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LMAID Laboratory, Universite Mohammed V de Rabat Ecole Mohammadia d'Ingenieurs, Rabat, Morocco","institution_ids":["https://openalex.org/I126477371","https://openalex.org/I127336678"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083034608","display_name":"El Moukhtar Zemmouri","orcid":"https://orcid.org/0000-0001-9165-0858"},"institutions":[{"id":"https://openalex.org/I4210153608","display_name":"Universit\u00e9 Moulay Ismail de Meknes","ror":"https://ror.org/04cnscd67","country_code":"MA","type":"education","lineage":["https://openalex.org/I4210153608"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Elmoukhtar Zemmouri","raw_affiliation_strings":["Department of Mathematics and Computer Science, University Moulay Ismail, ENSAM, Meknes, Morocco"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Computer Science, University Moulay Ismail, ENSAM, Meknes, Morocco","institution_ids":["https://openalex.org/I4210153608"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2709,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.65373941,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":"16","issue":"2","first_page":"223","last_page":"247"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9987999796867371,"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":0.9987999796867371,"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/T10028","display_name":"Topic Modeling","score":0.9980999827384949,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9959999918937683,"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/computer-science","display_name":"Computer science","score":0.800911545753479},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6430035829544067},{"id":"https://openalex.org/keywords/rdf","display_name":"RDF","score":0.6263980865478516},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.49063077569007874},{"id":"https://openalex.org/keywords/word2vec","display_name":"Word2vec","score":0.49007928371429443},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4596620798110962},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4569339156150818},{"id":"https://openalex.org/keywords/originality","display_name":"Originality","score":0.44335541129112244},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.327501505613327},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32743117213249207},{"id":"https://openalex.org/keywords/semantic-web","display_name":"Semantic Web","score":0.2536134719848633},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.21880397200584412}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.800911545753479},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6430035829544067},{"id":"https://openalex.org/C147497476","wikidata":"https://www.wikidata.org/wiki/Q54872","display_name":"RDF","level":3,"score":0.6263980865478516},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49063077569007874},{"id":"https://openalex.org/C2776461190","wikidata":"https://www.wikidata.org/wiki/Q22673982","display_name":"Word2vec","level":3,"score":0.49007928371429443},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4596620798110962},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4569339156150818},{"id":"https://openalex.org/C2776950860","wikidata":"https://www.wikidata.org/wiki/Q2914681","display_name":"Originality","level":3,"score":0.44335541129112244},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.327501505613327},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32743117213249207},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.2536134719848633},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.21880397200584412},{"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/C11012388","wikidata":"https://www.wikidata.org/wiki/Q170658","display_name":"Creativity","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1108/ijwis-10-2019-0048","is_oa":false,"landing_page_url":"https://doi.org/10.1108/ijwis-10-2019-0048","pdf_url":null,"source":{"id":"https://openalex.org/S145159096","display_name":"International Journal of Web Information Systems","issn_l":"1744-0084","issn":["1744-0084","1744-0092"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319811","host_organization_name":"Emerald Publishing Limited","host_organization_lineage":["https://openalex.org/P4310319811"],"host_organization_lineage_names":["Emerald Publishing Limited"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Web Information Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":66,"referenced_works":["https://openalex.org/W4154683","https://openalex.org/W150699991","https://openalex.org/W172136067","https://openalex.org/W285990849","https://openalex.org/W607263761","https://openalex.org/W1506109531","https://openalex.org/W1507579264","https://openalex.org/W1545331097","https://openalex.org/W1554936603","https://openalex.org/W1614298861","https://openalex.org/W1689688298","https://openalex.org/W1888005072","https://openalex.org/W1934051226","https://openalex.org/W1962869473","https://openalex.org/W1980285307","https://openalex.org/W1982767798","https://openalex.org/W1989009626","https://openalex.org/W2002505110","https://openalex.org/W2030194122","https://openalex.org/W2040022355","https://openalex.org/W2046318915","https://openalex.org/W2071516971","https://openalex.org/W2081101619","https://openalex.org/W2087159174","https://openalex.org/W2087962968","https://openalex.org/W2100417396","https://openalex.org/W2101746535","https://openalex.org/W2118891120","https://openalex.org/W2122865749","https://openalex.org/W2124228533","https://openalex.org/W2127795553","https://openalex.org/W2131744502","https://openalex.org/W2137219016","https://openalex.org/W2140119009","https://openalex.org/W2141599568","https://openalex.org/W2145544171","https://openalex.org/W2150874198","https://openalex.org/W2153579005","https://openalex.org/W2154851992","https://openalex.org/W2159793693","https://openalex.org/W2163598528","https://openalex.org/W2166366933","https://openalex.org/W2184957013","https://openalex.org/W2250539671","https://openalex.org/W2265073338","https://openalex.org/W2293312306","https://openalex.org/W2295578825","https://openalex.org/W2398511638","https://openalex.org/W2399155711","https://openalex.org/W2399448187","https://openalex.org/W2400638285","https://openalex.org/W2406720264","https://openalex.org/W2486503258","https://openalex.org/W2503375463","https://openalex.org/W2523679382","https://openalex.org/W2612872092","https://openalex.org/W2662322907","https://openalex.org/W2768535638","https://openalex.org/W2808935172","https://openalex.org/W2894207346","https://openalex.org/W2909823311","https://openalex.org/W2917785830","https://openalex.org/W2962756421","https://openalex.org/W3003770903","https://openalex.org/W3104097132","https://openalex.org/W4244207479"],"related_works":["https://openalex.org/W2593155302","https://openalex.org/W2041415459","https://openalex.org/W3126095231","https://openalex.org/W2072812638","https://openalex.org/W2352855287","https://openalex.org/W2378906650","https://openalex.org/W2384288445","https://openalex.org/W2382526412","https://openalex.org/W4200071106","https://openalex.org/W2347474189"],"abstract_inverted_index":{"Purpose":[0],"The":[1,34,58,151,227,264],"purpose":[2],"of":[3,24,73,80,95,143,157,170,172,195,229,280],"this":[4,230],"paper":[5,231],"is":[6,245,262],"to":[7,19,42,49,91,122,139,251,274,289],"present":[8],"a":[9,21,237],"generic":[10],"pipeline":[11,241],"for":[12,220,242],"Resource":[13],"Description":[14],"Framework":[15],"(RDF)":[16],"graph":[17,69,256,261],"mining":[18],"provide":[20],"comprehensive":[22],"review":[23],"each":[25,144],"step":[26],"in":[27,193,233],"the":[28,51,65,85,96,115,118,124,128,131,136,141,148,155,158,168,184,200,203,209,212,222,276,281,290],"knowledge":[29],"discovery":[30],"from":[31,46,135,258],"data":[32,160,224,244],"process.":[33],"authors":[35,66,86,116,129],"also":[36],"investigate":[37],"different":[38,270],"approaches":[39],"and":[40,53,78,105,164,176,191,253,278],"combinations":[41],"extract":[43,92,130,254],"feature":[44,283],"vectors":[45,94,284],"RDF":[47,125,243,260],"graphs":[48],"apply":[50],"clustering":[52,185,291],"theme":[54,145,201],"identification":[55],"tasks.":[56],"Design/methodology/approach":[57],"proposed":[59,265],"methodology":[60],"comprises":[61],"four":[62],"steps.":[63],"First,":[64],"generate":[67],"several":[68],"substructures":[70,257],"(Walks,":[71],"Set":[72,79,171],"Walks,":[74],"Walks":[75,81],"with":[76,82,108,174,269],"backward":[77],"backward).":[83],"Second,":[84],"build":[87],"neural":[88,271],"language":[89,272],"models":[90,273],"numerical":[93],"generated":[97],"sequences":[98],"by":[99,146,207],"using":[100,208],"word":[101],"embedding":[102],"techniques":[103,178,266],"(Word2Vec":[104],"Doc2Vec)":[106],"combined":[107,268],"term":[109],"frequency-inverse":[110],"document":[111],"frequency":[112],"(TF-IDF).":[113],"Third,":[114],"use":[117],"well-known":[119],"K-means":[120],"algorithm":[121],"cluster":[123],"graph.":[126],"Finally,":[127],"most":[132],"relevant":[133,255],"rdf:type":[134],"grouped":[137],"vertices":[138],"describe":[140],"semantics":[142],"generating":[147],"labels.":[149],"Findings":[150],"experimental":[152],"evaluation":[153],"on":[154],"state":[156],"art":[159],"sets":[161],"(AIFB,":[162],"BGS":[163],"Conference)":[165],"shows":[166],"that":[167,206,285],"combination":[169],"Walks-with-backward":[173],"TF-IDF":[175],"Doc2vec":[177],"give":[179],"excellent":[180],"results.":[181],"In":[182],"fact,":[183],"results":[186,204],"reach":[187,216],"more":[188,217],"than":[189,218],"97%":[190],"90%":[192,219],"terms":[194],"purity":[196,213],"andF-measure,":[197],"respectively.":[198],"Concerning":[199],"identification,":[202],"show":[205],"same":[210],"combination,":[211],"andF-measure":[214],"criteria":[215],"all":[221],"considered":[223],"sets.":[225],"Originality/value":[226],"originality":[228],"lies":[232],"two":[234],"aspects:":[235],"first,":[236],"new":[238],"machine":[239],"learning":[240],"presented;":[246],"second,":[247],"an":[248,259],"efficient":[249],"process":[250],"identify":[252],"proposed.":[263],"were":[267],"improve":[275],"accuracy":[277],"relevance":[279],"obtained":[282],"will":[286],"be":[287],"fed":[288],"mechanism.":[292]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}