{"id":"https://openalex.org/W1970183398","doi":"https://doi.org/10.1145/2505515.2505538","title":"Exploring weakly supervised latent sentiment explanations for aspect-level review analysis","display_name":"Exploring weakly supervised latent sentiment explanations for aspect-level review analysis","publication_year":2013,"publication_date":"2013-10-27","ids":{"openalex":"https://openalex.org/W1970183398","doi":"https://doi.org/10.1145/2505515.2505538","mag":"1970183398"},"language":"en","primary_location":{"id":"doi:10.1145/2505515.2505538","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2505515.2505538","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 international conference on Information & Knowledge Management","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/A5033174228","display_name":"Lei Fang","orcid":"https://orcid.org/0000-0003-2510-1281"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Fang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044042138","display_name":"Minlie Huang","orcid":"https://orcid.org/0000-0001-7111-1849"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minlie Huang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100452974","display_name":"Xiaoyan Zhu","orcid":"https://orcid.org/0000-0002-7173-7793"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyan Zhu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":2.5169,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.90599224,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1057","last_page":"1066"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T10664","display_name":"Sentiment Analysis and Opinion Mining","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":0.9958999752998352,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9860000014305115,"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/sentiment-analysis","display_name":"Sentiment analysis","score":0.8072672486305237},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7585282325744629},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6504217386245728},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6039705872535706},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5959222912788391},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.5768921375274658},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5533386468887329},{"id":"https://openalex.org/keywords/polarity","display_name":"Polarity (international relations)","score":0.5464493036270142},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3458919823169708}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.8072672486305237},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7585282325744629},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6504217386245728},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6039705872535706},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5959222912788391},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.5768921375274658},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5533386468887329},{"id":"https://openalex.org/C2777361361","wikidata":"https://www.wikidata.org/wiki/Q1112585","display_name":"Polarity (international relations)","level":3,"score":0.5464493036270142},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3458919823169708},{"id":"https://openalex.org/C1491633281","wikidata":"https://www.wikidata.org/wiki/Q7868","display_name":"Cell","level":2,"score":0.0},{"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/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2505515.2505538","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2505515.2505538","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 international conference on Information & Knowledge Management","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":39,"referenced_works":["https://openalex.org/W159038999","https://openalex.org/W1581485226","https://openalex.org/W1880262756","https://openalex.org/W1969486090","https://openalex.org/W1971889796","https://openalex.org/W1998257453","https://openalex.org/W2001587475","https://openalex.org/W2020818097","https://openalex.org/W2021891520","https://openalex.org/W2039813705","https://openalex.org/W2044429219","https://openalex.org/W2101534792","https://openalex.org/W2101769206","https://openalex.org/W2104474473","https://openalex.org/W2113786470","https://openalex.org/W2123713131","https://openalex.org/W2124022436","https://openalex.org/W2127467141","https://openalex.org/W2128507180","https://openalex.org/W2129604374","https://openalex.org/W2129894900","https://openalex.org/W2138260386","https://openalex.org/W2141631351","https://openalex.org/W2147102238","https://openalex.org/W2147196093","https://openalex.org/W2154970197","https://openalex.org/W2156693754","https://openalex.org/W2156953626","https://openalex.org/W2159457224","https://openalex.org/W2159737176","https://openalex.org/W2160409620","https://openalex.org/W2160660844","https://openalex.org/W2161228561","https://openalex.org/W2165664073","https://openalex.org/W2166344365","https://openalex.org/W2166706824","https://openalex.org/W2166765763","https://openalex.org/W2250838246","https://openalex.org/W2429914308"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2358755282","https://openalex.org/W2625833328","https://openalex.org/W2548633793","https://openalex.org/W1533177136","https://openalex.org/W1984947604"],"abstract_inverted_index":{"In":[0,25,59],"sentiment":[1,38,62,85],"analysis,":[2,36],"aspect-level":[3,34],"review":[4,35,67],"analysis":[5],"has":[6],"been":[7],"an":[8],"important":[9],"task":[10],"because":[11],"it":[12],"can":[13],"catalogue,":[14],"aggregate,":[15],"or":[16],"summarize":[17],"various":[18],"opinions":[19],"according":[20],"to":[21],"a":[22,30,44,66,80,98],"product's":[23],"properties.":[24],"this":[26],"paper,":[27],"we":[28,112],"explore":[29],"new":[31],"concept":[32],"for":[33],"latent":[37,90],"explanations,":[39],"which":[40,111],"are":[41,52,87,94],"defined":[42],"as":[43,79],"set":[45,99],"of":[46,56,70,100],"informative":[47],"aspect-specific":[48],"sentences":[49],"whose":[50],"polarities":[51],"consistent":[53],"with":[54,89],"that":[55],"the":[57,77,114],"review.":[58],"other":[60],"words,":[61],"explanations":[63,86],"best":[64],"represent":[65],"in":[68],"terms":[69,104],"both":[71],"aspect":[72,102],"and":[73,84],"polarity.":[74],"We":[75],"formulate":[76],"problem":[78],"structure":[81],"learning":[82],"problem,":[83],"modeled":[88],"variables.":[91],"Training":[92],"samples":[93],"automatically":[95],"identified":[96],"through":[97],"pre-defined":[101],"signature":[103],"(i.e.,":[105],"without":[106],"manual":[107],"annotation":[108],"on":[109],"samples),":[110],"term":[113],"way":[115],"weakly":[116],"supervised.":[117]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}