{"id":"https://openalex.org/W2077335893","doi":"https://doi.org/10.1145/2806416.2806533","title":"An Inference Approach to Basic Level of Categorization","display_name":"An Inference Approach to Basic Level of Categorization","publication_year":2015,"publication_date":"2015-10-17","ids":{"openalex":"https://openalex.org/W2077335893","doi":"https://doi.org/10.1145/2806416.2806533","mag":"2077335893"},"language":"en","primary_location":{"id":"doi:10.1145/2806416.2806533","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2806416.2806533","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM International on Conference on Information and Knowledge Management","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/A5100741750","display_name":"Zhongyuan Wang","orcid":"https://orcid.org/0000-0002-9796-488X"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhongyuan Wang","raw_affiliation_strings":["Renmin University of China & Microsoft Research, Beijing, China","Renmin University of China & Microsoft Research, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Renmin University of China & Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I78988378"]},{"raw_affiliation_string":"Renmin University of China & Microsoft Research, Beijing, China#TAB#","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063351917","display_name":"Haixun Wang","orcid":"https://orcid.org/0009-0007-0773-7004"},"institutions":[{"id":"https://openalex.org/I4210099336","display_name":"Menlo School","ror":"https://ror.org/01240pn49","country_code":"US","type":"education","lineage":["https://openalex.org/I4210099336"]},{"id":"https://openalex.org/I4210114444","display_name":"Meta (United States)","ror":"https://ror.org/01zbnvs85","country_code":"US","type":"company","lineage":["https://openalex.org/I4210114444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haixun Wang","raw_affiliation_strings":["Facebook, Menlo Park, USA","[Facebook, Menlo Park, USA]"],"affiliations":[{"raw_affiliation_string":"Facebook, Menlo Park, USA","institution_ids":["https://openalex.org/I4210114444","https://openalex.org/I4210099336"]},{"raw_affiliation_string":"[Facebook, Menlo Park, USA]","institution_ids":["https://openalex.org/I4210114444","https://openalex.org/I4210099336"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025631695","display_name":"Ji-Rong Wen","orcid":"https://orcid.org/0000-0002-9777-9676"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji-Rong Wen","raw_affiliation_strings":["Renmin University of China, Beijing, China","Renmin Univ. of China, Beijing - China#TAB#"],"affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]},{"raw_affiliation_string":"Renmin Univ. of China, Beijing - China#TAB#","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090455375","display_name":"Yanghua Xiao","orcid":"https://orcid.org/0000-0001-8403-9591"},"institutions":[{"id":"https://openalex.org/I24943067","display_name":"Fudan University","ror":"https://ror.org/013q1eq08","country_code":"CN","type":"education","lineage":["https://openalex.org/I24943067"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanghua Xiao","raw_affiliation_strings":["Fudan University, Shanghai, China","Fudan University Shanghai, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]},{"raw_affiliation_string":"Fudan University Shanghai, China#TAB#","institution_ids":["https://openalex.org/I24943067"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100741750"],"corresponding_institution_ids":["https://openalex.org/I78988378"],"apc_list":null,"apc_paid":null,"fwci":6.9031,"has_fulltext":false,"cited_by_count":67,"citation_normalized_percentile":{"value":0.96880714,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"653","last_page":"662"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9991999864578247,"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":0.9991999864578247,"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/T10181","display_name":"Natural Language Processing Techniques","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"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9957000017166138,"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":0.8145483136177063},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.7651559710502625},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6951838731765747},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5907690525054932},{"id":"https://openalex.org/keywords/subconscious","display_name":"Subconscious","score":0.5741426944732666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4959960877895355},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.44240546226501465},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.41129374504089355},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4079759120941162},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4018402397632599},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3301942050457001}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8145483136177063},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.7651559710502625},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6951838731765747},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5907690525054932},{"id":"https://openalex.org/C96851999","wikidata":"https://www.wikidata.org/wiki/Q848369","display_name":"Subconscious","level":3,"score":0.5741426944732666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4959960877895355},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.44240546226501465},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.41129374504089355},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4079759120941162},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4018402397632599},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3301942050457001},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C204787440","wikidata":"https://www.wikidata.org/wiki/Q188504","display_name":"Alternative medicine","level":2,"score":0.0},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2806416.2806533","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2806416.2806533","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM International on Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6000000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1491611863","https://openalex.org/W1495062271","https://openalex.org/W1505839237","https://openalex.org/W1512387364","https://openalex.org/W1514107797","https://openalex.org/W1548461347","https://openalex.org/W1574901103","https://openalex.org/W1614298861","https://openalex.org/W1872023060","https://openalex.org/W1880262756","https://openalex.org/W1964838558","https://openalex.org/W1965069660","https://openalex.org/W2022166150","https://openalex.org/W2038721957","https://openalex.org/W2055460448","https://openalex.org/W2059799772","https://openalex.org/W2068737686","https://openalex.org/W2094625154","https://openalex.org/W2094728533","https://openalex.org/W2107743791","https://openalex.org/W2115461474","https://openalex.org/W2120779048","https://openalex.org/W2135251234","https://openalex.org/W2138605095","https://openalex.org/W2147152072","https://openalex.org/W2152444902","https://openalex.org/W2158899491","https://openalex.org/W2164385956","https://openalex.org/W2252137719","https://openalex.org/W2293188561","https://openalex.org/W2600077159","https://openalex.org/W2803437449","https://openalex.org/W2997617958","https://openalex.org/W4233135949","https://openalex.org/W4235505822","https://openalex.org/W4255280018","https://openalex.org/W6682656196","https://openalex.org/W6997569583"],"related_works":["https://openalex.org/W3132110389","https://openalex.org/W2392683697","https://openalex.org/W4207004974","https://openalex.org/W4385360431","https://openalex.org/W2514389873","https://openalex.org/W2353486471","https://openalex.org/W2972168326","https://openalex.org/W34139413","https://openalex.org/W3015062709","https://openalex.org/W2083817658"],"abstract_inverted_index":{"Humans":[0],"understand":[1,113],"the":[2,74,122],"world":[3],"by":[4],"classifying":[5],"objects":[6],"into":[7],"an":[8,50],"appropriate":[9],"level":[10],"of":[11,33,124],"categories.":[12],"This":[13],"process":[14],"is":[15,48],"often":[16],"automatic":[17],"and":[18,21,40,94,109,116],"subconscious.":[19],"Psychologists":[20],"linguists":[22],"call":[23],"it":[24,71,100],"as":[25,36,107],"Basic-level":[26],"Categorization":[27],"(BLC).":[28],"BLC":[29,137],"can":[30,138],"benefit":[31],"lots":[32],"applications":[34],"such":[35,106],"knowledge":[37,59],"panel,":[38],"advertising":[39],"recommendation.":[41],"However,":[42],"how":[43,136],"to":[44,77,112,120,134],"quantify":[45],"basic-level":[46],"concepts":[47],"still":[49],"open":[51],"problem.":[52],"Recently,":[53],"much":[54],"work":[55],"focuses":[56],"on":[57,92],"constructing":[58],"bases":[60],"or":[61],"semantic":[62],"networks":[63],"from":[64],"web":[65],"scale":[66],"text":[67],"corpora,":[68],"which":[69],"makes":[70],"possible":[72],"for":[73,81,96],"first":[75],"time":[76,111],"analyze":[78],"computational":[79],"approaches":[80],"deriving":[82],"BLC.":[83,97],"In":[84],"this":[85],"paper,":[86],"we":[87],"introduce":[88],"a":[89,102,130],"method":[90],"based":[91],"typicality":[93],"PMI":[95],"We":[98,127],"compare":[99],"with":[101],"few":[103],"existing":[104],"measures":[105],"NPMI":[108],"commute":[110],"its":[114],"essence,":[115],"conduct":[117],"extensive":[118],"experiments":[119],"show":[121,135],"effectiveness":[123],"our":[125],"approach.":[126],"also":[128],"give":[129],"real":[131],"application":[132],"example":[133],"help":[139],"sponsored":[140],"search.":[141]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":11},{"year":2019,"cited_by_count":14},{"year":2018,"cited_by_count":12},{"year":2017,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}