{"id":"https://openalex.org/W2093337383","doi":"https://doi.org/10.1109/nlpke.2010.5587797","title":"An improved method of keywords extraction based on short technology text","display_name":"An improved method of keywords extraction based on short technology text","publication_year":2010,"publication_date":"2010-08-01","ids":{"openalex":"https://openalex.org/W2093337383","doi":"https://doi.org/10.1109/nlpke.2010.5587797","mag":"2093337383"},"language":"en","primary_location":{"id":"doi:10.1109/nlpke.2010.5587797","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2010.5587797","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100384838","display_name":"Jun Wang","orcid":"https://orcid.org/0000-0002-9515-076X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]},{"id":"https://openalex.org/I922474255","display_name":"Tokushima University","ror":"https://ror.org/044vy1d05","country_code":"JP","type":"education","lineage":["https://openalex.org/I922474255"]}],"countries":["CN","JP"],"is_corresponding":false,"raw_author_name":"Jun Wang","raw_affiliation_strings":["Faculty of Engineering, University of Tokushima, Tokushima, Japan","School of Computer, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Tokushima, Tokushima, Japan","institution_ids":["https://openalex.org/I922474255"]},{"raw_affiliation_string":"School of Computer, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440301","display_name":"Lei Li","orcid":"https://orcid.org/0000-0002-3204-6527"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Li","raw_affiliation_strings":["School of Computer, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071943346","display_name":"Fuji Ren","orcid":"https://orcid.org/0000-0003-4860-9184"},"institutions":[{"id":"https://openalex.org/I922474255","display_name":"Tokushima University","ror":"https://ror.org/044vy1d05","country_code":"JP","type":"education","lineage":["https://openalex.org/I922474255"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Fuji Ren","raw_affiliation_strings":["Faculty of Engineering, University of Tokushima, Tokushima, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, University of Tokushima, Tokushima, Japan","institution_ids":["https://openalex.org/I922474255"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.20563926,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"13","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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/T13734","display_name":"Advanced Computational Techniques and Applications","score":0.9099000096321106,"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":0.8378905057907104},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6697779893875122},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6328269839286804},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.6205441355705261},{"id":"https://openalex.org/keywords/text-segmentation","display_name":"Text segmentation","score":0.6042158007621765},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5502694249153137},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.5415018796920776},{"id":"https://openalex.org/keywords/keyword-extraction","display_name":"Keyword extraction","score":0.48878857493400574},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.47045719623565674},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.4659510552883148},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4325443506240845},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43012911081314087},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.426617830991745},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4107244610786438},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37160128355026245},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32850778102874756},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07857516407966614}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8378905057907104},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6697779893875122},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6328269839286804},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.6205441355705261},{"id":"https://openalex.org/C98501671","wikidata":"https://www.wikidata.org/wiki/Q1948408","display_name":"Text segmentation","level":3,"score":0.6042158007621765},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5502694249153137},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.5415018796920776},{"id":"https://openalex.org/C2780288562","wikidata":"https://www.wikidata.org/wiki/Q25053353","display_name":"Keyword extraction","level":2,"score":0.48878857493400574},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.47045719623565674},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.4659510552883148},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4325443506240845},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43012911081314087},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.426617830991745},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4107244610786438},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37160128355026245},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32850778102874756},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07857516407966614},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/nlpke.2010.5587797","is_oa":false,"landing_page_url":"https://doi.org/10.1109/nlpke.2010.5587797","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1980300096","https://openalex.org/W2036701977","https://openalex.org/W2064418625","https://openalex.org/W2115898140","https://openalex.org/W2165200277","https://openalex.org/W2351317893","https://openalex.org/W2352214567","https://openalex.org/W2358516765","https://openalex.org/W2360916879","https://openalex.org/W2370585626","https://openalex.org/W2380482579","https://openalex.org/W2391927950","https://openalex.org/W6684434663","https://openalex.org/W6705916609","https://openalex.org/W6708533844"],"related_works":["https://openalex.org/W2357647850","https://openalex.org/W2393940967","https://openalex.org/W2385598138","https://openalex.org/W2346578824","https://openalex.org/W2366925922","https://openalex.org/W2159591557","https://openalex.org/W2115592387","https://openalex.org/W2905950556","https://openalex.org/W2112534334","https://openalex.org/W120168696"],"abstract_inverted_index":{"Keywords":[0],"are":[1],"the":[2,23,40,53,61,70,83,90,96,103],"critical":[3],"resources":[4],"of":[5,25,31,42,55,63,78,105],"information":[6],"management":[7],"and":[8,13,101,108],"retrieval,":[9],"automatic":[10],"text":[11],"classification":[12],"clustering.":[14],"The":[15],"keywords":[16,32,57,79,106],"extraction":[17,33,80],"plays":[18],"an":[19,75],"important":[20],"role":[21],"in":[22,36,60],"process":[24],"constructing":[26],"structured":[27],"text.":[28,65],"Current":[29],"algorithms":[30],"have":[34,50],"matured":[35],"some":[37],"ways.":[38],"However":[39],"errors":[41,97],"word":[43],"segmentation":[44,100],"which":[45],"caused":[46,98],"by":[47,99],"unknown":[48],"words":[49],"been":[51],"affected":[52],"performance":[54,104],"Chinese":[56],"extraction,":[58,107],"particularly":[59],"field":[62],"technological":[64],"In":[66],"order":[67],"to":[68,113],"solve":[69],"problem,":[71],"this":[72],"paper":[73],"proposes":[74],"improved":[76],"method":[77,92],"based":[81],"on":[82],"relationship":[84],"among":[85],"words.":[86],"Experiments":[87],"show":[88],"that":[89],"proposed":[91],"can":[93,110],"effectively":[94],"correct":[95],"improve":[102],"it":[109],"also":[111],"extend":[112],"other":[114],"areas.":[115]},"counts_by_year":[{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}