{"id":"https://openalex.org/W2971191450","doi":"https://doi.org/10.1145/3357384.3357989","title":"Cross-domain Aspect Category Transfer and Detection via Traceable Heterogeneous Graph Representation Learning","display_name":"Cross-domain Aspect Category Transfer and Detection via Traceable Heterogeneous Graph Representation Learning","publication_year":2019,"publication_date":"2019-11-03","ids":{"openalex":"https://openalex.org/W2971191450","doi":"https://doi.org/10.1145/3357384.3357989","mag":"2971191450"},"language":"en","primary_location":{"id":"doi:10.1145/3357384.3357989","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3357384.3357989","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1908.11610","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Zhuoren Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhuoren Jiang","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jian Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Wang","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lujun Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lujun Zhao","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Changlong Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I45928872","display_name":"Alibaba Group (China)","ror":"https://ror.org/00k642b80","country_code":"CN","type":"company","lineage":["https://openalex.org/I45928872"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changlong Sun","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yao Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Lu","raw_affiliation_strings":["Sun Yat-sen University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":null,"display_name":"Xiaozhong Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210119109","display_name":"Indiana University Bloomington","ror":"https://ror.org/02k40bc56","country_code":"US","type":"education","lineage":["https://openalex.org/I4210119109","https://openalex.org/I592451"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaozhong Liu","raw_affiliation_strings":["Indiana University Bloomington, Bloomington, IN, USA"],"affiliations":[{"raw_affiliation_string":"Indiana University Bloomington, Bloomington, IN, USA","institution_ids":["https://openalex.org/I4210119109"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157773358"],"apc_list":null,"apc_paid":null,"fwci":0.578,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.75993318,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"289","last_page":"298"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9990000128746033,"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":0.9979000091552734,"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/categorical-variable","display_name":"Categorical variable","score":0.8154000043869019},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.603600025177002},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5522000193595886},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5342000126838684},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.47350001335144043},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4715000092983246},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4578000009059906},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4255000054836273},{"id":"https://openalex.org/keywords/random-walk","display_name":"Random walk","score":0.39399999380111694},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.3910999894142151}],"concepts":[{"id":"https://openalex.org/C5274069","wikidata":"https://www.wikidata.org/wiki/Q2285707","display_name":"Categorical variable","level":2,"score":0.8154000043869019},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6281999945640564},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.603600025177002},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5522000193595886},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5342000126838684},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5116999745368958},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.47350001335144043},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4715000092983246},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4578000009059906},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4255000054836273},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39719998836517334},{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.39399999380111694},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.3910999894142151},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.3684999942779541},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.3580999970436096},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.35199999809265137},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3476000130176544},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33799999952316284},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.33410000801086426},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3337000012397766},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.3199000060558319},{"id":"https://openalex.org/C90673727","wikidata":"https://www.wikidata.org/wiki/Q901718","display_name":"Product (mathematics)","level":2,"score":0.2973000109195709},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.2892000079154968},{"id":"https://openalex.org/C65965080","wikidata":"https://www.wikidata.org/wiki/Q1806885","display_name":"Latent variable model","level":3,"score":0.28769999742507935},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.26750001311302185},{"id":"https://openalex.org/C147101817","wikidata":"https://www.wikidata.org/wiki/Q13443840","display_name":"Product category","level":3,"score":0.2639000117778778},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.25440001487731934},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.25429999828338623}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3357384.3357989","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3357384.3357989","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Information and Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1908.11610","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.11610","pdf_url":"https://arxiv.org/pdf/1908.11610","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1908.11610","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1908.11610","pdf_url":"https://arxiv.org/pdf/1908.11610","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1404860586","display_name":null,"funder_award_id":"18lgpy62","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"}],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W103340358","https://openalex.org/W1622600386","https://openalex.org/W1832693441","https://openalex.org/W1880262756","https://openalex.org/W1888005072","https://openalex.org/W2001259128","https://openalex.org/W2034852725","https://openalex.org/W2096110600","https://openalex.org/W2146341620","https://openalex.org/W2153353890","https://openalex.org/W2154851992","https://openalex.org/W2160660844","https://openalex.org/W2174706414","https://openalex.org/W2238728730","https://openalex.org/W2251792193","https://openalex.org/W2252057809","https://openalex.org/W2395579298","https://openalex.org/W2465978385","https://openalex.org/W2470673105","https://openalex.org/W2507887397","https://openalex.org/W2740567223","https://openalex.org/W2743104969","https://openalex.org/W2758375579","https://openalex.org/W2798621783","https://openalex.org/W2895924502","https://openalex.org/W2962756421","https://openalex.org/W2963168371","https://openalex.org/W2964275331","https://openalex.org/W3003665436"],"related_works":[],"abstract_inverted_index":{"Aspect":[0],"category":[1,48,92],"detection":[2,85],"is":[3,110],"an":[4,72,104],"essential":[5],"task":[6],"for":[7,26],"sentiment":[8],"analysis":[9],"and":[10,50,62,118,145],"opinion":[11],"mining.":[12],"However,":[13],"the":[14,22,114,120,124,154],"cost":[15],"of":[16,30,160],"categorical":[17],"data":[18,60,143],"labeling,":[19],"e.g.,":[20],"label":[21],"review":[23],"aspect":[24,47,84,91],"information":[25,98],"a":[27,43,100,138,158],"large":[28],"number":[29],"product":[31],"domains,":[32],"can":[33],"be":[34],"inevitable":[35],"but":[36],"unaffordable.":[37],"In":[38],"this":[39],"study,":[40],"we":[41,70,131],"propose":[42,71],"novel":[44],"problem,":[45],"cross-domain":[46],"transfer":[49],"detection,":[51],"which":[52],"faces":[53],"three":[54],"challenges:":[55],"various":[56],"feature":[57,135],"spaces,":[58],"different":[59,133],"distributions,":[61],"diverse":[63],"output":[64,146],"spaces.":[65],"To":[66],"address":[67],"these":[68],"problems,":[69],"innovative":[73,105],"solution,":[74],"Traceable":[75],"Heterogeneous":[76],"Graph":[77],"Representation":[78],"Learning":[79],"(THGRL).":[80],"Unlike":[81],"prior":[82],"text-based":[83],"works,":[86],"THGRL":[87],"explores":[88],"latent":[89,106],"domain":[90],"connections":[93],"via":[94],"massive":[95],"user":[96],"behavior":[97],"on":[99,123],"heterogeneous":[101],"graph.":[102],"Moreover,":[103],"variable":[107],"\"Walker":[108],"Tracer\"":[109],"introduced":[111],"to":[112],"characterize":[113],"global":[115],"semantic/aspect":[116],"dependencies":[117],"capture":[119],"informative":[121],"vertexes":[122],"random":[125],"walk":[126],"paths.":[127],"By":[128],"using":[129],"THGRL,":[130],"project":[132],"domains'":[134],"spaces":[136,147],"into":[137],"common":[139],"one,":[140],"while":[141],"allowing":[142],"distributions":[144],"stay":[148],"differently.":[149],"Experiment":[150],"results":[151],"show":[152],"that":[153],"proposed":[155],"method":[156],"outperforms":[157],"series":[159],"state-of-the-art":[161],"baseline":[162],"models.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2019-09-05T00:00:00"}
