{"id":"https://openalex.org/W2016015339","doi":"https://doi.org/10.1145/2505515.2505556","title":"A partially supervised cross-collection topic model for cross-domain text classification","display_name":"A partially supervised cross-collection topic model for cross-domain text classification","publication_year":2013,"publication_date":"2013-10-27","ids":{"openalex":"https://openalex.org/W2016015339","doi":"https://doi.org/10.1145/2505515.2505556","mag":"2016015339"},"language":"en","primary_location":{"id":"doi:10.1145/2505515.2505556","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2505515.2505556","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":"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/A5000974879","display_name":"Yang Bao","orcid":"https://orcid.org/0000-0001-9868-4946"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Yang Bao","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073413742","display_name":"Nigel Collier","orcid":"https://orcid.org/0000-0002-7230-4164"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Nigel Collier","raw_affiliation_strings":["National Institute of Informatics, Tokyo, Japan","(National Institute of Informatics, Tokyo, Japan)"],"affiliations":[{"raw_affiliation_string":"National Institute of Informatics, Tokyo, Japan","institution_ids":["https://openalex.org/I184597095"]},{"raw_affiliation_string":"(National Institute of Informatics, Tokyo, Japan)","institution_ids":["https://openalex.org/I184597095"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035863623","display_name":"Anindya Datta","orcid":"https://orcid.org/0000-0001-7966-2944"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Anindya Datta","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5000974879"],"corresponding_institution_ids":["https://openalex.org/I165932596"],"apc_list":null,"apc_paid":null,"fwci":5.7752,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.957731,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"239","last_page":"248"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9993000030517578,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9993000030517578,"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/T10028","display_name":"Topic Modeling","score":0.9977999925613403,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9803000092506409,"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/classifier","display_name":"Classifier (UML)","score":0.8048469424247742},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7796023488044739},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6783491969108582},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5770073533058167},{"id":"https://openalex.org/keywords/marginal-distribution","display_name":"Marginal distribution","score":0.4707888960838318},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46113860607147217},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.45660924911499023},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44979193806648254},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.44514769315719604},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4310861825942993},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3316672444343567},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13432759046554565},{"id":"https://openalex.org/keywords/random-variable","display_name":"Random variable","score":0.06798011064529419},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06777900457382202}],"concepts":[{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.8048469424247742},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7796023488044739},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6783491969108582},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5770073533058167},{"id":"https://openalex.org/C165216359","wikidata":"https://www.wikidata.org/wiki/Q670653","display_name":"Marginal distribution","level":3,"score":0.4707888960838318},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46113860607147217},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.45660924911499023},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44979193806648254},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.44514769315719604},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4310861825942993},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3316672444343567},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13432759046554565},{"id":"https://openalex.org/C122123141","wikidata":"https://www.wikidata.org/wiki/Q176623","display_name":"Random variable","level":2,"score":0.06798011064529419},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06777900457382202},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2505515.2505556","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2505515.2505556","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"},{"id":"pmh:oai:scholarbank.nus.edu.sg:10635/77971","is_oa":false,"landing_page_url":"http://scholarbank.nus.edu.sg/handle/10635/77971","pdf_url":null,"source":{"id":"https://openalex.org/S7407052290","display_name":"National University of Singapore","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.4699999988079071,"display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320327550","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W665341","https://openalex.org/W1536816303","https://openalex.org/W1880262756","https://openalex.org/W1970275213","https://openalex.org/W1985615910","https://openalex.org/W2001082470","https://openalex.org/W2061806977","https://openalex.org/W2068463433","https://openalex.org/W2112247328","https://openalex.org/W2118585731","https://openalex.org/W2131953535","https://openalex.org/W2134731454","https://openalex.org/W2141114446","https://openalex.org/W2141443306","https://openalex.org/W2143374704","https://openalex.org/W2153353890","https://openalex.org/W2158108973","https://openalex.org/W2163302275","https://openalex.org/W2165698076","https://openalex.org/W2398879410","https://openalex.org/W2589887588","https://openalex.org/W3001645704","https://openalex.org/W6679554340"],"related_works":["https://openalex.org/W2982642565","https://openalex.org/W2113421559","https://openalex.org/W3204418343","https://openalex.org/W1560624709","https://openalex.org/W3144173820","https://openalex.org/W1996537998","https://openalex.org/W3214142563","https://openalex.org/W3166286441","https://openalex.org/W4221162086","https://openalex.org/W3111760155"],"abstract_inverted_index":{"Cross-domain":[0],"text":[1,9,18],"classification":[2],"aims":[3],"to":[4,35,99,113],"automatically":[5],"train":[6],"a":[7,12,21,37,52,124,146],"precise":[8],"classifier":[10,55],"for":[11,134],"target":[13],"domain":[14],"by":[15],"using":[16],"labelled":[17],"data":[19],"from":[20],"related":[22],"source":[23,92],"domain.":[24,93],"To":[25],"this":[26,60,120],"end,":[27],"one":[28],"of":[29,73,77,83,140,170],"the":[30,43,71,74,80,91,102,110,116,138,168],"most":[31,65],"promising":[32],"ideas":[33],"is":[34],"induce":[36],"new":[38,61],"feature":[39,62],"representation":[40],"so":[41],"that":[42,155],"distributional":[44],"difference":[45],"between":[46],"domains":[47],"can":[48,56],"be":[49,57],"reduced":[50],"and":[51,79,104,108,162],"more":[53],"accurate":[54],"learned":[58],"in":[59,90,145],"space.":[63],"However,":[64],"existing":[66],"methods":[67],"do":[68],"not":[69],"explore":[70],"duality":[72],"marginal":[75],"distribution":[76,82],"examples":[78,89],"conditional":[81],"class":[84],"labels":[85],"given":[86],"labeled":[87],"training":[88],"Besides,":[94],"few":[95],"previous":[96],"works":[97],"attempt":[98],"explicitly":[100],"distinguish":[101],"domain-independent":[103],"domain-specific":[105,111],"latent":[106],"features":[107,112],"align":[109],"further":[114],"improve":[115],"cross-domain":[117,135],"learning.":[118],"In":[119],"paper,":[121],"we":[122],"propose":[123],"model":[125,132,157],"called":[126],"Partially":[127],"Supervised":[128],"Cross-Collection":[129],"LDA":[130],"topic":[131],"(PSCCLDA)":[133],"learning":[136],"with":[137],"purpose":[139],"addressing":[141],"these":[142],"two":[143,159],"issues":[144],"unified":[147],"way.":[148],"Experimental":[149],"results":[150],"on":[151],"nine":[152],"datasets":[153],"show":[154],"our":[156,171],"outperforms":[158],"standard":[160],"classifiers":[161],"four":[163],"state-of-the-art":[164],"methods,":[165],"which":[166],"demonstrates":[167],"effectiveness":[169],"proposed":[172],"model.":[173]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":3}],"updated_date":"2026-03-01T08:55:55.761014","created_date":"2025-10-10T00:00:00"}