{"id":"https://openalex.org/W2075368020","doi":"https://doi.org/10.1145/1995966.1996002","title":"Entity set expansion in opinion documents","display_name":"Entity set expansion in opinion documents","publication_year":2011,"publication_date":"2011-06-06","ids":{"openalex":"https://openalex.org/W2075368020","doi":"https://doi.org/10.1145/1995966.1996002","mag":"2075368020"},"language":"en","primary_location":{"id":"doi:10.1145/1995966.1996002","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1995966.1996002","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM conference on Hypertext and hypermedia","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/A5106578837","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0002-5305-8543"},"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":true,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100339927","display_name":"Bing Liu","orcid":"https://orcid.org/0000-0002-4096-6980"},"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":"Bing Liu","raw_affiliation_strings":["University of Illinois at Chicago, Chicago, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, Chicago, USA","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5106578837"],"corresponding_institution_ids":["https://openalex.org/I39422238"],"apc_list":null,"apc_paid":null,"fwci":1.7103,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.86655121,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"281","last_page":"290"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","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/T10028","display_name":"Topic Modeling","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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9994999766349792,"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":0.9994000196456909,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7905198931694031},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.7328701019287109},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6427432298660278},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5912575125694275},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5811545252799988},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5596912503242493},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.5448992848396301},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5392732620239258},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5372177958488464},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5071866512298584},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5065821409225464},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5030967593193054},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4277821183204651},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.380365788936615},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3555644452571869},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22740432620048523}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7905198931694031},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.7328701019287109},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6427432298660278},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5912575125694275},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5811545252799988},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5596912503242493},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5448992848396301},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5392732620239258},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5372177958488464},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5071866512298584},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5065821409225464},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5030967593193054},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4277821183204651},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.380365788936615},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3555644452571869},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22740432620048523},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1995966.1996002","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1995966.1996002","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM conference on Hypertext and hypermedia","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":36,"referenced_works":["https://openalex.org/W197270748","https://openalex.org/W1493490255","https://openalex.org/W1505544955","https://openalex.org/W1508170391","https://openalex.org/W1541579345","https://openalex.org/W1604957788","https://openalex.org/W2035432878","https://openalex.org/W2050712820","https://openalex.org/W2068737686","https://openalex.org/W2093812930","https://openalex.org/W2096259344","https://openalex.org/W2097726431","https://openalex.org/W2103296194","https://openalex.org/W2103931177","https://openalex.org/W2104987630","https://openalex.org/W2113958117","https://openalex.org/W2115346359","https://openalex.org/W2117400858","https://openalex.org/W2120084270","https://openalex.org/W2126581182","https://openalex.org/W2129629757","https://openalex.org/W2129712609","https://openalex.org/W2141099517","https://openalex.org/W2142984157","https://openalex.org/W2147880316","https://openalex.org/W2148540243","https://openalex.org/W2154496970","https://openalex.org/W2163780445","https://openalex.org/W2166776180","https://openalex.org/W2170682101","https://openalex.org/W2284650288","https://openalex.org/W2293997450","https://openalex.org/W2913389685","https://openalex.org/W4205184193","https://openalex.org/W4231741839","https://openalex.org/W4255198209"],"related_works":["https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W2596247554","https://openalex.org/W3132372214","https://openalex.org/W4224284088","https://openalex.org/W4286571989","https://openalex.org/W2765903680","https://openalex.org/W4317653575","https://openalex.org/W2801635251"],"abstract_inverted_index":{"Opinion":[0],"mining":[1,55,97,250],"has":[2,132],"been":[3],"an":[4,61],"active":[5],"research":[6],"area":[7],"in":[8],"recent":[9],"years.":[10],"The":[11,76,130],"task":[12],"is":[13,48,60,72,78,89,153,174],"to":[14,80,102,133,200,224,235,239,263,287],"extract":[15],"opinions":[16,104],"expressed":[17],"on":[18,39,54,105,166,275],"entities":[19,56,145],"and":[20,213,238],"their":[21],"attributes.":[22],"For":[23,216,228],"example,":[24],"the":[25,29,40,49,67,69,81,99,135,143,149,154,162,226,241,249,261,304,307],"sentence,":[26],"\"I":[27],"love":[28],"picture":[30,41],"quality":[31,42,242],"of":[32,44,73,128,148,243,267,278,306],"Sony":[33,45,47],"cameras,\"":[34],"expresses":[35],"a":[36,90,94,120,138,179,196,221,265],"positive":[37],"opinion":[38,71,96],"attribute":[43],"cameras.":[46],"entity.":[50],"This":[51,59,140,152,204],"paper":[52],"focuses":[53],"(e.g.,":[57],"Sony).":[58],"important":[62],"problem":[63,77,163],"because":[64],"without":[65],"knowing":[66],"entity,":[68],"extracted":[70],"little":[74],"use.":[75],"similar":[79],"classic":[82],"named":[83],"entity":[84,211,217],"recognition":[85],"problem.":[86,157,227],"However,":[87,114,169,185],"there":[88,124],"major":[91,209],"difference.":[92],"In":[93],"typical":[95],"application,":[98],"user":[100,262],"wants":[101],"find":[103,134],"some":[106,271],"competing":[107,110],"entities,":[108],"e.g.,":[109],"or":[111],"relevant":[112],"products.":[113],"he/she":[115],"often":[116],"can":[117],"only":[118],"provide":[119],"few":[121],"names":[122],"as":[123],"are":[125,164],"too":[126],"many":[127],"them.":[129],"system":[131],"rest":[136],"from":[137,300],"corpus.":[139],"implies":[141],"that":[142],"discovered":[144],"must":[146],"be":[147],"same":[150],"type/class.":[151],"set":[155,266],"expansion":[156],"Classic":[158],"methods":[159,234,246],"for":[160,280,290],"solving":[161],"based":[165,274],"distributional":[167],"similarity.":[168],"we":[170,219,231],"found":[171],"this":[172],"method":[173,181,223],"inaccurate.":[175],"We":[176,193,269],"then":[177,194],"employ":[178],"learning-based":[180],"called":[182],"Bayesian":[183,188,202,258],"Sets.":[184,203],"directly":[186],"applying":[187],"Sets":[189,259],"produces":[190],"poor":[191],"results.":[192],"propose":[195,220,232],"more":[197],"sophisticated":[198],"way":[199],"use":[201],"method,":[205],"however,":[206],"causes":[207],"two":[208,233],"problems:":[210],"ranking":[212],"feature":[214,229],"sparseness.":[215],"ranking,":[218],"re-ranking":[222],"solve":[225],"sparseness,":[230],"re-weight":[236],"features":[237,273,289],"determine":[240],"features.":[244,268],"These":[245],"help":[247],"improve":[248],"results":[251,295],"substantially.":[252],"Additionally,":[253],"like":[254],"any":[255],"learning":[256],"algorithm,":[257],"requires":[260],"engineer":[264,288],"design":[270],"generic":[272],"part-of-speech":[276],"tags":[277],"words":[279],"learning,":[281],"which":[282],"thus":[283],"does":[284],"not":[285],"need":[286],"each":[291],"specific":[292],"domain.":[293],"Experimental":[294],"using":[296],"10":[297],"real-life":[298],"datasets":[299],"diverse":[301],"domains":[302],"demonstrated":[303],"effectiveness":[305],"proposed":[308],"technique.":[309]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":20},{"year":2018,"cited_by_count":1},{"year":2015,"cited_by_count":13},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
