{"id":"https://openalex.org/W2911988918","doi":"https://doi.org/10.1145/3289600.3291039","title":"Weakly Supervised Co-Training of Query Rewriting andSemantic Matching for e-Commerce","display_name":"Weakly Supervised Co-Training of Query Rewriting andSemantic Matching for e-Commerce","publication_year":2019,"publication_date":"2019-01-30","ids":{"openalex":"https://openalex.org/W2911988918","doi":"https://doi.org/10.1145/3289600.3291039","mag":"2911988918"},"language":"en","primary_location":{"id":"doi:10.1145/3289600.3291039","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3289600.3291039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining","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/A5114321253","display_name":"Rong Xiao","orcid":"https://orcid.org/0000-0001-7793-6040"},"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":true,"raw_author_name":"Rong Xiao","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":"https://openalex.org/A5023690189","display_name":"Jianhui Ji","orcid":"https://orcid.org/0000-0002-1344-145X"},"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":"Jianhui Ji","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":"https://openalex.org/A5102303867","display_name":"Baoliang Cui","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":"Baoliang Cui","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":"https://openalex.org/A5101669398","display_name":"Haihong Tang","orcid":"https://orcid.org/0000-0002-7103-975X"},"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":"Haihong Tang","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":"https://openalex.org/A5004601283","display_name":"Wenwu Ou","orcid":"https://orcid.org/0009-0004-2437-6835"},"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":"Wenwu Ou","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":"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"],"affiliations":[{"raw_affiliation_string":"Fudan University, Shanghai, China","institution_ids":["https://openalex.org/I24943067"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077784320","display_name":"Jiwei Tan","orcid":"https://orcid.org/0009-0004-4028-5570"},"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":"Jiwei Tan","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078209927","display_name":"Xuan Ju","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":"Xuan Ju","raw_affiliation_strings":["Alibaba Group, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Alibaba Group, Hangzhou, China","institution_ids":["https://openalex.org/I45928872"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5114321253"],"corresponding_institution_ids":["https://openalex.org/I45928872"],"apc_list":null,"apc_paid":null,"fwci":4.4088,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.94867124,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"402","last_page":"410"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9986000061035156,"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"}},"topics":[{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9986000061035156,"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"}},{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9962999820709229,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9958000183105469,"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":0.8677785396575928},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.7868845462799072},{"id":"https://openalex.org/keywords/semantic-matching","display_name":"Semantic matching","score":0.7268933057785034},{"id":"https://openalex.org/keywords/rewriting","display_name":"Rewriting","score":0.6717240214347839},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5501958131790161},{"id":"https://openalex.org/keywords/semantic-gap","display_name":"Semantic gap","score":0.5285305380821228},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5219268798828125},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4663739800453186},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.4631684720516205},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43062078952789307},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.4293728470802307},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3444199860095978},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.10266602039337158},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.0981699526309967}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8677785396575928},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.7868845462799072},{"id":"https://openalex.org/C2778493491","wikidata":"https://www.wikidata.org/wiki/Q7449072","display_name":"Semantic matching","level":3,"score":0.7268933057785034},{"id":"https://openalex.org/C154690210","wikidata":"https://www.wikidata.org/wiki/Q1668499","display_name":"Rewriting","level":2,"score":0.6717240214347839},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5501958131790161},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.5285305380821228},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5219268798828125},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4663739800453186},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.4631684720516205},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43062078952789307},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.4293728470802307},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3444199860095978},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.10266602039337158},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.0981699526309967},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3289600.3291039","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3289600.3291039","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining","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":23,"referenced_works":["https://openalex.org/W1505796919","https://openalex.org/W1966443646","https://openalex.org/W1979459060","https://openalex.org/W2045865594","https://openalex.org/W2052088591","https://openalex.org/W2079168273","https://openalex.org/W2104049510","https://openalex.org/W2126250169","https://openalex.org/W2131876387","https://openalex.org/W2136189984","https://openalex.org/W2142920810","https://openalex.org/W2167660864","https://openalex.org/W2533180076","https://openalex.org/W2536015822","https://openalex.org/W2610935556","https://openalex.org/W2613589950","https://openalex.org/W2766284073","https://openalex.org/W2793652880","https://openalex.org/W2809897079","https://openalex.org/W3098851962","https://openalex.org/W3122775348","https://openalex.org/W3212575067","https://openalex.org/W4231856373"],"related_works":["https://openalex.org/W2120204135","https://openalex.org/W2139396251","https://openalex.org/W1796293478","https://openalex.org/W1577544887","https://openalex.org/W2168276503","https://openalex.org/W3205408642","https://openalex.org/W2584816862","https://openalex.org/W2157224911","https://openalex.org/W2389678293","https://openalex.org/W3183710995"],"abstract_inverted_index":{"Relevance":[0],"is":[1,15,26,36],"the":[2,12,16,50,67,72,80,93,110,131,142,179,183],"core":[3],"problem":[4,25,113],"of":[5,11,82,141,167],"a":[6,105,122,165,173],"search":[7,127,176],"engine,":[8,177],"and":[9,22,41,70,99,103,169,178],"one":[10],"main":[13],"challenges":[14],"vocabulary":[17],"gap":[18,52],"between":[19,53,96],"user":[20],"queries":[21],"documents.":[23],"This":[24],"more":[27,37],"serious":[28],"in":[29,33,85],"e-commerce,":[30],"because":[31],"language":[32],"product":[34],"titles":[35],"professional.":[38],"Query":[39],"rewriting":[40,98],"semantic":[42,51,100],"matching":[43,101],"are":[44],"two":[45,68,132,138],"key":[46],"techniques":[47],"to":[48,55,66,108,158],"bridge":[49],"them":[54,149],"improve":[56],"relevance.":[57],"Recently,":[58],"deep":[59,116],"neural":[60,117],"networks":[61],"have":[62],"been":[63],"successfully":[64],"applied":[65],"tasks":[69,133],"enhanced":[71],"relevance":[73,143,187],"performance.":[74],"However,":[75],"such":[76],"approaches":[77],"suffer":[78],"from":[79,126,154],"sparseness":[81,112],"training":[83,115],"data":[84,111,152],"e-commerce":[86,175],"scenario.":[87],"In":[88],"this":[89,155],"study,":[90],"we":[91,146],"investigate":[92],"instinctive":[94],"connection":[95],"query":[97],"tasks,":[102],"propose":[104],"co-training":[106],"framework":[107],"address":[109],"when":[114],"networks.":[118],"We":[119,163],"first":[120],"build":[121],"huge":[123],"unlabeled":[124,156],"dataset":[125],"logs,":[128],"on":[129,172],"which":[130],"can":[134],"be":[135],"considered":[136],"as":[137],"different":[139],"views":[140],"problem.":[144],"Then":[145],"iteratively":[147],"co-train":[148],"via":[150],"labeled":[151],"generated":[153],"set":[157],"boost":[159],"their":[160],"performance":[161],"simultaneously.":[162],"conduct":[164],"series":[166],"offline":[168],"online":[170],"experiments":[171],"real-world":[174],"results":[180],"demonstrate":[181],"that":[182],"proposed":[184],"method":[185],"improves":[186],"significantly.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}