{"id":"https://openalex.org/W2810430765","doi":"https://doi.org/10.1109/fskd.2017.8393033","title":"A novel keyphrase extraction method by combining FP-growth and LDA","display_name":"A novel keyphrase extraction method by combining FP-growth and LDA","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2810430765","doi":"https://doi.org/10.1109/fskd.2017.8393033","mag":"2810430765"},"language":"en","primary_location":{"id":"doi:10.1109/fskd.2017.8393033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2017.8393033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","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/A5101865390","display_name":"Hao Sun","orcid":"https://orcid.org/0000-0003-3238-8225"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hao Sun","raw_affiliation_strings":["International School of Software, Wuhan University Wuhan, China"],"affiliations":[{"raw_affiliation_string":"International School of Software, Wuhan University Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100451253","display_name":"Bing Li","orcid":"https://orcid.org/0000-0002-2165-2636"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bing Li","raw_affiliation_strings":["International School of Software, Wuhan University Wuhan, China"],"affiliations":[{"raw_affiliation_string":"International School of Software, Wuhan University Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047240103","display_name":"Bo Han","orcid":"https://orcid.org/0000-0002-6338-0958"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Han","raw_affiliation_strings":["International School of Software, Wuhan University Wuhan, China"],"affiliations":[{"raw_affiliation_string":"International School of Software, Wuhan University Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101865390"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.2356823,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"19","issue":null,"first_page":"1764","last_page":"1768"},"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"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.953499972820282,"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9337000250816345,"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/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.8938896656036377},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8711555004119873},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.6020716428756714},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5511665344238281},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.45927104353904724},{"id":"https://openalex.org/keywords/the-internet","display_name":"The Internet","score":0.45319944620132446},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3771964907646179},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3698708415031433},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.34521520137786865},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.10390934348106384}],"concepts":[{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.8938896656036377},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8711555004119873},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.6020716428756714},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5511665344238281},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.45927104353904724},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.45319944620132446},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3771964907646179},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3698708415031433},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.34521520137786865},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.10390934348106384}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fskd.2017.8393033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fskd.2017.8393033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.49000000953674316,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1598801360","https://openalex.org/W1880262756","https://openalex.org/W1942403956","https://openalex.org/W1969486090","https://openalex.org/W2018079881","https://openalex.org/W2018409826","https://openalex.org/W2032906216","https://openalex.org/W2064853889","https://openalex.org/W2081895858","https://openalex.org/W2105745072","https://openalex.org/W2127000941","https://openalex.org/W2163659824","https://openalex.org/W2514072522","https://openalex.org/W4252403066","https://openalex.org/W6639619044"],"related_works":["https://openalex.org/W2769501189","https://openalex.org/W4315588616","https://openalex.org/W4312773271","https://openalex.org/W2888805565","https://openalex.org/W2962686197","https://openalex.org/W2207653751","https://openalex.org/W3005513013","https://openalex.org/W2611137333","https://openalex.org/W4291700620","https://openalex.org/W4317422773"],"abstract_inverted_index":{"Fast-growing":[0],"technologies":[1],"like":[2],"cloud-computing,":[3],"big":[4],"data,":[5],"mobile":[6],"Internet,":[7],"artificial":[8],"intelligence,":[9],"etc.":[10],"have":[11,82],"driven":[12],"the":[13,46,64,85,98],"emergences":[14],"of":[15,18],"a":[16,26],"lot":[17],"new":[19],"phrases.":[20,62],"In":[21,45,63],"this":[22],"paper,":[23],"we":[24,49,67],"propose":[25],"novel":[27],"keyphrases":[28,70,91],"extraction":[29],"method":[30],"with":[31],"two":[32,77],"steps":[33],"by":[34,71],"combining":[35],"FP-growth":[36,51],"algorithm":[37,52],"and":[38,80,92],"Latent":[39],"Dirichlet":[40],"Allocation":[41],"(LDA)":[42],"topic":[43],"modeling.":[44],"first":[47],"step,":[48,66],"apply":[50],"to":[53],"obtain":[54],"frequent":[55],"neighborhood":[56],"words":[57],"co-occurring":[58],"frequently":[59],"as":[60],"candidate":[61],"second":[65],"extract":[68,89],"significant":[69,90],"LDA":[72],"models.":[73],"Our":[74],"experiments":[75],"on":[76],"datasets":[78],"CVE-2015":[79],"20-newsgroups":[81],"shown":[83],"that":[84],"proposed":[86],"approach":[87],"can":[88,95],"these":[93],"phrases":[94],"help":[96],"improve":[97],"text":[99],"classification":[100],"accuracy.":[101]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}