{"id":"https://openalex.org/W2987154886","doi":"https://doi.org/10.1145/3360901.3364447","title":"Exploring Word Embeddings in CRF-based Keyphrase Extraction from Research Papers","display_name":"Exploring Word Embeddings in CRF-based Keyphrase Extraction from Research Papers","publication_year":2019,"publication_date":"2019-09-23","ids":{"openalex":"https://openalex.org/W2987154886","doi":"https://doi.org/10.1145/3360901.3364447","mag":"2987154886"},"language":"en","primary_location":{"id":"doi:10.1145/3360901.3364447","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3360901.3364447","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3360901.3364447","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Conference on Knowledge Capture","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3360901.3364447","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059069001","display_name":"Krutarth Patel","orcid":null},"institutions":[{"id":"https://openalex.org/I189590672","display_name":"Kansas State University","ror":"https://ror.org/05p1j8758","country_code":"US","type":"education","lineage":["https://openalex.org/I189590672"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Krutarth Patel","raw_affiliation_strings":["Kansas State University, Manhattan, KS, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kansas State University, Manhattan, KS, USA","institution_ids":["https://openalex.org/I189590672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089085275","display_name":"Cornelia Caragea","orcid":"https://orcid.org/0000-0002-5664-2163"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cornelia Caragea","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"37","last_page":"44"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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":0.7781357169151306},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6744964122772217},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6521269679069519},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5335239768028259},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.327402800321579}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7781357169151306},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6744964122772217},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6521269679069519},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5335239768028259},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.327402800321579},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3360901.3364447","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3360901.3364447","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3360901.3364447","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Conference on Knowledge Capture","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3360901.3364447","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3360901.3364447","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3360901.3364447","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th International Conference on Knowledge Capture","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1765179195","display_name":"CRI: CI-SUSTAIN: Collaborative Research: CiteSeerX: Toward Sustainable Support of Scholarly Big Data","funder_award_id":"1823292","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4313431862","display_name":null,"funder_award_id":"1823292, 1652674","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7004516563","display_name":"CAREER: From Data to Knowledge: Extracting and Utilizing Concept Graphs in Online Environments","funder_award_id":"1802358","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2987154886.pdf","grobid_xml":"https://content.openalex.org/works/W2987154886.grobid-xml"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W32253530","https://openalex.org/W168564468","https://openalex.org/W171888312","https://openalex.org/W1490343430","https://openalex.org/W1525595230","https://openalex.org/W1544240449","https://openalex.org/W1890164900","https://openalex.org/W1894735736","https://openalex.org/W1907578970","https://openalex.org/W1940872118","https://openalex.org/W2030903088","https://openalex.org/W2045181608","https://openalex.org/W2050763348","https://openalex.org/W2064418625","https://openalex.org/W2097385711","https://openalex.org/W2102733276","https://openalex.org/W2136652593","https://openalex.org/W2141222516","https://openalex.org/W2144512097","https://openalex.org/W2145049651","https://openalex.org/W2146769536","https://openalex.org/W2147880316","https://openalex.org/W2156577800","https://openalex.org/W2157979304","https://openalex.org/W2158139315","https://openalex.org/W2160517426","https://openalex.org/W2162250788","https://openalex.org/W2163659824","https://openalex.org/W2167329753","https://openalex.org/W2175961425","https://openalex.org/W2250527440","https://openalex.org/W2250589143","https://openalex.org/W2250954789","https://openalex.org/W2251009376","https://openalex.org/W2251476947","https://openalex.org/W2251955066","https://openalex.org/W2400193661","https://openalex.org/W2566297247","https://openalex.org/W2566480286","https://openalex.org/W2604912255","https://openalex.org/W2608018997","https://openalex.org/W2742094278","https://openalex.org/W2804950764","https://openalex.org/W2888466689","https://openalex.org/W2888766462","https://openalex.org/W2890179025","https://openalex.org/W2914076857","https://openalex.org/W2914848704","https://openalex.org/W2934664789","https://openalex.org/W2950133940","https://openalex.org/W2950635152","https://openalex.org/W2950982165","https://openalex.org/W2962676330","https://openalex.org/W2962903510","https://openalex.org/W2963265326","https://openalex.org/W2963275829","https://openalex.org/W3000068678","https://openalex.org/W4285719527","https://openalex.org/W4298232866"],"related_works":["https://openalex.org/W2360025963","https://openalex.org/W2370299677","https://openalex.org/W2611614995","https://openalex.org/W2360785147","https://openalex.org/W2368651715","https://openalex.org/W2789919619","https://openalex.org/W1552159754","https://openalex.org/W2148757832","https://openalex.org/W3107474891","https://openalex.org/W1508636238"],"abstract_inverted_index":{"Keyphrases":[0],"associated":[1],"with":[2,27,91,111,132],"research":[3,124],"papers":[4,125],"provide":[5],"an":[6],"effective":[7],"way":[8],"to":[9,33,75],"find":[10],"useful":[11],"information":[12],"in":[13,58,89,95],"the":[14,28,52,69,76,83,97,128],"large":[15],"and":[16,50,139],"growing":[17],"scholarly":[18],"digital":[19],"collections.":[20],"However,":[21],"keyphrases":[22,99],"are":[23],"not":[24],"always":[25],"provided":[26],"papers,":[29],"but":[30],"they":[31],"need":[32],"be":[34],"extracted":[35],"from":[36,72],"their":[37],"content.":[38],"In":[39],"this":[40,144],"paper,":[41],"we":[42,104],"explore":[43,105],"keyphrase":[44,116],"extraction":[45],"formulated":[46],"as":[47,108],"sequence":[48],"labeling":[49],"utilize":[51],"power":[53],"of":[54,68,123],"Conditional":[55],"Random":[56],"Fields":[57],"capturing":[59],"label":[60,74],"dependencies":[61],"through":[62],"a":[63,101],"transition":[64,70],"parameter":[65],"matrix":[66],"consisting":[67],"probabilities":[71],"one":[73],"neighboring":[77],"label.":[78],"We":[79],"aim":[80],"at":[81],"identifying":[82],"features":[84,109,114,135],"that,":[85],"by":[86],"themselves":[87],"or":[88],"combination":[90],"others,":[92],"perform":[93],"well":[94],"extracting":[96],"descriptive":[98],"for":[100,115,143],"paper.":[102],"Specifically,":[103],"word":[106,129],"embeddings":[107,130],"along":[110],"traditional,":[112],"document-specific":[113],"extraction.":[117],"Our":[118],"results":[119],"on":[120],"five":[121],"datasets":[122],"show":[126],"that":[127],"combined":[131],"document":[133],"specific":[134],"achieve":[136],"high":[137],"performance":[138],"outperform":[140],"strong":[141],"baselines":[142],"task.":[145]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
