{"id":"https://openalex.org/W4205528052","doi":"https://doi.org/10.1145/3494560","title":"Domain-Specific Keyword Extraction Using Joint Modeling of Local and Global Contextual Semantics","display_name":"Domain-Specific Keyword Extraction Using Joint Modeling of Local and Global Contextual Semantics","publication_year":2022,"publication_date":"2022-01-08","ids":{"openalex":"https://openalex.org/W4205528052","doi":"https://doi.org/10.1145/3494560"},"language":"en","primary_location":{"id":"doi:10.1145/3494560","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3494560","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","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/A5079913042","display_name":"Muhammad Abulaish","orcid":"https://orcid.org/0000-0003-3387-4743"},"institutions":[{"id":"https://openalex.org/I90425906","display_name":"South Asian University","ror":"https://ror.org/02kjyst95","country_code":"IN","type":"education","lineage":["https://openalex.org/I90425906"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Muhammad Abulaish","raw_affiliation_strings":["South Asian University, Chanakyapuri, New Delhi, India"],"raw_orcid":"https://orcid.org/0000-0003-3387-4743","affiliations":[{"raw_affiliation_string":"South Asian University, Chanakyapuri, New Delhi, India","institution_ids":["https://openalex.org/I90425906"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012975536","display_name":"Mohd Fazil","orcid":"https://orcid.org/0000-0002-8936-848X"},"institutions":[{"id":"https://openalex.org/I90425906","display_name":"South Asian University","ror":"https://ror.org/02kjyst95","country_code":"IN","type":"education","lineage":["https://openalex.org/I90425906"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Mohd Fazil","raw_affiliation_strings":["South Asian University, Chanakyapuri, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South Asian University, Chanakyapuri, New Delhi, India","institution_ids":["https://openalex.org/I90425906"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019559411","display_name":"Mohammed J. Zaki","orcid":"https://orcid.org/0000-0003-4711-0234"},"institutions":[{"id":"https://openalex.org/I165799507","display_name":"Rensselaer Polytechnic Institute","ror":"https://ror.org/01rtyzb94","country_code":"US","type":"education","lineage":["https://openalex.org/I165799507"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mohammed J. Zaki","raw_affiliation_strings":["Rensselaer Polytechnic Institute, Troy, NY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rensselaer Polytechnic Institute, Troy, NY","institution_ids":["https://openalex.org/I165799507"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.3188,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.89383452,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"16","issue":"4","first_page":"1","last_page":"30"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":1.0,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":1.0,"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":0.9642000198364258,"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":0.963699996471405,"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":0.8553479909896851},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5857029557228088},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5798356533050537},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5574011206626892},{"id":"https://openalex.org/keywords/pagerank","display_name":"PageRank","score":0.5481899976730347},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5245932936668396},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.512069046497345},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.4505876898765564},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.44950640201568604},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.448882520198822},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43229860067367554},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.4160749614238739},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.0953841507434845}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8553479909896851},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5857029557228088},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5798356533050537},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5574011206626892},{"id":"https://openalex.org/C2779172887","wikidata":"https://www.wikidata.org/wiki/Q184316","display_name":"PageRank","level":2,"score":0.5481899976730347},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5245932936668396},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.512069046497345},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.4505876898765564},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.44950640201568604},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.448882520198822},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43229860067367554},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.4160749614238739},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.0953841507434845},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3494560","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3494560","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6100000143051147,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W80619934","https://openalex.org/W1486781940","https://openalex.org/W1596452184","https://openalex.org/W1854214752","https://openalex.org/W1880262756","https://openalex.org/W1965961515","https://openalex.org/W1973646734","https://openalex.org/W1980499355","https://openalex.org/W1982442952","https://openalex.org/W2015469910","https://openalex.org/W2037124106","https://openalex.org/W2040467972","https://openalex.org/W2049023511","https://openalex.org/W2064418625","https://openalex.org/W2066636486","https://openalex.org/W2071747526","https://openalex.org/W2080068076","https://openalex.org/W2081580037","https://openalex.org/W2093138961","https://openalex.org/W2102046030","https://openalex.org/W2107434887","https://openalex.org/W2144211451","https://openalex.org/W2159457224","https://openalex.org/W2167329753","https://openalex.org/W2250539671","https://openalex.org/W2398936787","https://openalex.org/W2511832088","https://openalex.org/W2554439417","https://openalex.org/W2566297247","https://openalex.org/W2740811004","https://openalex.org/W2772993019","https://openalex.org/W2790740913","https://openalex.org/W2796219422","https://openalex.org/W2804950764","https://openalex.org/W2887178861","https://openalex.org/W2897012459","https://openalex.org/W2909945613","https://openalex.org/W2926825864","https://openalex.org/W2928032745","https://openalex.org/W2944847455","https://openalex.org/W2949678053","https://openalex.org/W2950100256","https://openalex.org/W2962750587","https://openalex.org/W2963265326","https://openalex.org/W2963345057","https://openalex.org/W2972650346","https://openalex.org/W2992548114","https://openalex.org/W2998704965","https://openalex.org/W3139886635","https://openalex.org/W4213228826","https://openalex.org/W4231307919","https://openalex.org/W4297904282","https://openalex.org/W6603330179"],"related_works":["https://openalex.org/W2888662092","https://openalex.org/W3205826705","https://openalex.org/W2903394456","https://openalex.org/W2902285665","https://openalex.org/W3119550360","https://openalex.org/W2975174210","https://openalex.org/W4200238620","https://openalex.org/W2244029015","https://openalex.org/W2287843335","https://openalex.org/W2754876402"],"abstract_inverted_index":{"Domain-specific":[0],"keyword":[1,45,113],"extraction":[2,46],"is":[3,39,186],"a":[4,32,55,87,117,121,131,141,154,169,182],"vital":[5],"task":[6],"in":[7,78,226],"the":[8,61,93,102,127,137,149,163,174,178,189,193,199,238],"field":[9],"of":[10,34,60,99,104,120,140,157,165,171,177,202],"text":[11,128,214],"mining.":[12],"There":[13],"are":[14],"various":[15],"research":[16],"tasks,":[17],"such":[18],"as":[19,130,153],"spam":[20],"e-mail":[21],"classification,":[22],"abusive":[23],"language":[24],"detection,":[25],"sentiment":[26],"analysis,":[27],"and":[28,74,95,108,162,212,219,241],"emotion":[29],"mining,":[30],"where":[31],"set":[33,119,201],"domain-specific":[35,52,112,123,203],"keywords":[36,49,53],"(aka":[37],"lexicon)":[38],"highly":[40],"effective.":[41],"Existing":[42],"works":[43],"for":[44,111,197],"list":[47],"all":[48],"rather":[50],"than":[51],"from":[54],"document":[56,68],"corpus.":[57],"Moreover,":[58],"most":[59,194],"existing":[62,246],"approaches":[63],"perform":[64],"well":[65],"on":[66,72],"formal":[67,211],"corpuses":[69,215],"but":[70],"fail":[71],"noisy":[73],"informal":[75,213],"user-generated":[76],"content":[77],"online":[79],"social":[80],"media.":[81],"In":[82,134],"this":[83,135],"article,":[84],"we":[85,125,232],"present":[86],"hybrid":[88],"approach":[89,235],"by":[90],"jointly":[91],"modeling":[92],"local":[94],"global":[96],"contextual":[97],"semantics":[98],"words,":[100],"utilizing":[101],"strength":[103],"distributional":[105],"word":[106],"representation":[107],"contrasting-domain":[109],"corpus":[110,129],"extraction.":[114],"Starting":[115],"with":[116,148],"seed":[118],"few":[122],"keywords,":[124],"model":[126],"weighted":[132],"word-graph.":[133],"graph,":[136],"initial":[138,200],"weight":[139,164],"node":[142],"(word)":[143],"represents":[144,173],"its":[145],"semantic":[146,159],"association":[147,160],"target":[150],"domain":[151],"calculated":[152],"linear":[155],"combination":[156],"three":[158],"metrics,":[161],"an":[166],"edge":[167],"connecting":[168],"pair":[170],"nodes":[172],"co-occurrence":[175],"count":[176],"respective":[179],"words.":[180],"Thereafter,":[181],"modified":[183],"PageRank":[184],"method":[185,208],"applied":[187],"to":[188,191,228,236],"word-graph":[190],"identify":[192],"relevant":[195],"words":[196],"expanding":[198],"keywords.":[204],"We":[205],"evaluate":[206],"our":[207,234],"over":[209],"both":[210],"(comprising":[216],"six":[217],"datasets),":[218],"show":[220,242],"that":[221,243],"it":[222,244],"performs":[223],"significantly":[224],"better":[225],"comparison":[227],"state-of-the-art":[229],"methods.":[230],"Furthermore,":[231],"generalize":[233],"handle":[237],"language-agnostic":[239,247],"case,":[240],"outperforms":[245],"approaches.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-17T09:13:05.818461","created_date":"2025-10-10T00:00:00"}
