{"id":"https://openalex.org/W1659908699","doi":"https://doi.org/10.1109/ijcnn.2015.7280513","title":"A word distributed representation based framework for large-scale short text classification","display_name":"A word distributed representation based framework for large-scale short text classification","publication_year":2015,"publication_date":"2015-07-01","ids":{"openalex":"https://openalex.org/W1659908699","doi":"https://doi.org/10.1109/ijcnn.2015.7280513","mag":"1659908699"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2015.7280513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2015.7280513","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Joint Conference on Neural Networks (IJCNN)","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/A5070236880","display_name":"Di Yao","orcid":"https://orcid.org/0000-0003-1778-8319"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Yao","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","Institute of Computing Technology , Chinese Academy of Sciences , Beijing 100190 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"raw_affiliation_string":"Institute of Computing Technology , Chinese Academy of Sciences , Beijing 100190 , China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102995513","display_name":"Jingping Bi","orcid":"https://orcid.org/0000-0001-7858-4980"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingping Bi","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","Institute of Computing Technology , Chinese Academy of Sciences , Beijing 100190 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"raw_affiliation_string":"Institute of Computing Technology , Chinese Academy of Sciences , Beijing 100190 , China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101859055","display_name":"Jianhui Huang","orcid":"https://orcid.org/0000-0002-5614-1019"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhui Huang","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","Institute of Computing Technology , Chinese Academy of Sciences , Beijing 100190 , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]},{"raw_affiliation_string":"Institute of Computing Technology , Chinese Academy of Sciences , Beijing 100190 , China","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046525114","display_name":"Jin Zhu","orcid":"https://orcid.org/0000-0001-8550-5822"},"institutions":[{"id":"https://openalex.org/I142861451","display_name":"Yunnan Nationalities University","ror":"https://ror.org/030jhb479","country_code":"CN","type":"education","lineage":["https://openalex.org/I142861451"]},{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Zhu","raw_affiliation_strings":["Yunnan University of Nationalities, Kunming, China","Yunnan University of Nationalities, Kunming, 650031 China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yunnan University of Nationalities, Kunming, China","institution_ids":["https://openalex.org/I142861451","https://openalex.org/I189210763"]},{"raw_affiliation_string":"Yunnan University of Nationalities, Kunming, 650031 China","institution_ids":["https://openalex.org/I189210763"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.823,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.72399178,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994000196456909,"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/T10028","display_name":"Topic Modeling","score":0.9994000196456909,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9984999895095825,"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":0.9983999729156494,"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":0.8395285606384277},{"id":"https://openalex.org/keywords/treebank","display_name":"Treebank","score":0.7697314620018005},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.677152156829834},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6358945965766907},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6357541680335999},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5970562100410461},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5948300957679749},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5507239103317261},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5503289103507996},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.5215620398521423},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.46730637550354004},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4099154472351074},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.11576715111732483},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.06809598207473755}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8395285606384277},{"id":"https://openalex.org/C206134035","wikidata":"https://www.wikidata.org/wiki/Q811525","display_name":"Treebank","level":3,"score":0.7697314620018005},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.677152156829834},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6358945965766907},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6357541680335999},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5970562100410461},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5948300957679749},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5507239103317261},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5503289103507996},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.5215620398521423},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.46730637550354004},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4099154472351074},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.11576715111732483},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.06809598207473755},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"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/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2015.7280513","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2015.7280513","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W27263903","https://openalex.org/W71569195","https://openalex.org/W100623710","https://openalex.org/W137112649","https://openalex.org/W1612003148","https://openalex.org/W1663973292","https://openalex.org/W1714665356","https://openalex.org/W1880262756","https://openalex.org/W2066302459","https://openalex.org/W2095122172","https://openalex.org/W2107535552","https://openalex.org/W2118585731","https://openalex.org/W2149684865","https://openalex.org/W2153579005","https://openalex.org/W2171836785","https://openalex.org/W2251939518","https://openalex.org/W2949547296"],"related_works":["https://openalex.org/W2740662036","https://openalex.org/W3142119062","https://openalex.org/W159209093","https://openalex.org/W589103562","https://openalex.org/W1991220724","https://openalex.org/W2251234095","https://openalex.org/W2114797768","https://openalex.org/W2380654781","https://openalex.org/W2176214140","https://openalex.org/W2516873349"],"abstract_inverted_index":{"With":[0],"the":[1,15,27,39,45,54,71,89,99,111,116,127,132,144,153,159,171,187,202,205],"development":[2],"of":[3,8,17,41,91,94,204],"internet,":[4],"there":[5],"are":[6],"billions":[7],"short":[9,20,56,85,101,118],"texts":[10,57],"generated":[11],"each":[12],"day.":[13],"However,":[14],"accuracy":[16],"large":[18,83,160,188],"scale":[19,84,161,189],"text":[21,86],"classification":[22,180],"is":[23,58],"poor":[24],"due":[25],"to":[26,33,37,60,69],"data":[28,46,72],"sparseness.":[29],"Traditional":[30],"methods":[31],"used":[32],"use":[34],"external":[35,50,77],"dataset":[36,51,165,193],"enrich":[38,126],"representation":[40,108,129],"document":[42,128],"and":[43,109,158],"solve":[44,70],"sparsity":[47,73],"problem.":[48],"But":[49],"which":[52,96,125,166],"matches":[53],"specific":[55],"hard":[59],"find.":[61],"In":[62],"this":[63],"paper,":[64],"we":[65,104,121,139,184],"propose":[66,122],"a":[67,123],"framework":[68,80,150,176,197],"problem":[74],"without":[75],"using":[76,131,174],"dataset.":[78],"Our":[79],"deal":[81],"with":[82,201],"by":[87,130,168],"making":[88],"most":[90],"semantic":[92,113,134],"similarity":[93,114,135],"words":[95],"learned":[97],"from":[98,115],"training":[100,117,206],"texts.":[102,119],"First,":[103],"learn":[105],"word":[106,112,133],"distributed":[107],"measure":[110],"Then,":[120],"method":[124],"information.":[136],"At":[137],"last,":[138],"build":[140],"classifiers":[141],"based":[142],"on":[143,151,186],"enriched":[145],"representation.":[146],"We":[147],"evaluate":[148],"our":[149,175,196],"both":[152],"benchmark":[154,172],"dataset(Standford":[155],"Sentiment":[156],"Treebank)":[157],"Chinese":[162,190],"news":[163,191],"title":[164,192],"collected":[167],"ourselves.":[169],"For":[170],"dataset,":[173],"can":[177],"improve":[178],"3%":[179],"accuracy.":[181],"The":[182],"result":[183,200],"tested":[185],"shows":[194],"that":[195],"achieve":[198],"better":[199],"increase":[203],"set":[207],"size.":[208]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
