{"id":"https://openalex.org/W2944927867","doi":"https://doi.org/10.1145/3292500.3330926","title":"Enhancing Domain Word Embedding via Latent Semantic Imputation","display_name":"Enhancing Domain Word Embedding via Latent Semantic Imputation","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2944927867","doi":"https://doi.org/10.1145/3292500.3330926","mag":"2944927867"},"language":"en","primary_location":{"id":"doi:10.1145/3292500.3330926","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330926","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1905.08900","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Shibo Yao","orcid":null},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shibo Yao","raw_affiliation_strings":["New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Dantong Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I118118575","display_name":"New Jersey Institute of Technology","ror":"https://ror.org/05e74xb87","country_code":"US","type":"education","lineage":["https://openalex.org/I118118575"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dantong Yu","raw_affiliation_strings":["New Jersey Institute of Technology, Newark, NJ, USA"],"affiliations":[{"raw_affiliation_string":"New Jersey Institute of Technology, Newark, NJ, USA","institution_ids":["https://openalex.org/I118118575"]}]},{"author_position":"last","author":{"id":null,"display_name":"Keli Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Keli Xiao","raw_affiliation_strings":["Stony Brook University, Stony Brook, NY, USA"],"affiliations":[{"raw_affiliation_string":"Stony Brook University, Stony Brook, NY, USA","institution_ids":["https://openalex.org/I59553526"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I118118575"],"apc_list":null,"apc_paid":null,"fwci":0.434,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.70924845,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"557","last_page":"565"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9995999932289124,"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":0.9922000169754028,"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/word-embedding","display_name":"Word embedding","score":0.6496000289916992},{"id":"https://openalex.org/keywords/imputation","display_name":"Imputation (statistics)","score":0.5942000150680542},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5490000247955322},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.40299999713897705},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.39649999141693115},{"id":"https://openalex.org/keywords/latent-semantic-analysis","display_name":"Latent semantic analysis","score":0.3718999922275543},{"id":"https://openalex.org/keywords/concreteness","display_name":"Concreteness","score":0.36000001430511475},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.3427000045776367}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6574000120162964},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.6496000289916992},{"id":"https://openalex.org/C58041806","wikidata":"https://www.wikidata.org/wiki/Q1660484","display_name":"Imputation (statistics)","level":3,"score":0.5942000150680542},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5490000247955322},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5403000116348267},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.43309998512268066},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.40299999713897705},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.39649999141693115},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.3718999922275543},{"id":"https://openalex.org/C2778436841","wikidata":"https://www.wikidata.org/wiki/Q5159081","display_name":"Concreteness","level":2,"score":0.36000001430511475},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.3427000045776367},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.33730000257492065},{"id":"https://openalex.org/C112933361","wikidata":"https://www.wikidata.org/wiki/Q2845258","display_name":"Probabilistic latent semantic analysis","level":2,"score":0.33640000224113464},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33070001006126404},{"id":"https://openalex.org/C186450821","wikidata":"https://www.wikidata.org/wiki/Q17295","display_name":"Euclidean space","level":2,"score":0.2996000051498413},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2660999894142151},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2630999982357025},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.2621999979019165},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.25380000472068787},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.2533000111579895}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3292500.3330926","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330926","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1905.08900","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1905.08900","pdf_url":"https://arxiv.org/pdf/1905.08900","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:1905.08900","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1905.08900","pdf_url":"https://arxiv.org/pdf/1905.08900","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":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1965680834","https://openalex.org/W2018428315","https://openalex.org/W2055981215","https://openalex.org/W2063532964","https://openalex.org/W2064675550","https://openalex.org/W2097308346","https://openalex.org/W2105831729","https://openalex.org/W2132914434","https://openalex.org/W2147152072","https://openalex.org/W2250539671","https://openalex.org/W2252211741","https://openalex.org/W2265846598","https://openalex.org/W2402268235","https://openalex.org/W2510403706","https://openalex.org/W2882319491","https://openalex.org/W2997185401","https://openalex.org/W2998704965","https://openalex.org/W4250803253"],"related_works":[],"abstract_inverted_index":{"We":[0,98,126],"present":[1],"a":[2,103],"novel":[3],"method":[4,22,51],"named":[5],"Latent":[6],"Semantic":[7],"Imputation":[8],"(LSI)":[9],"to":[10,26,52,63],"transfer":[11],"external":[12],"knowledge":[13],"into":[14],"semantic":[15,86],"space":[16,38,87],"for":[17,81],"enhancing":[18],"word":[19,96],"embedding.":[20,97],"The":[21],"integrates":[23],"graph":[24],"theory":[25],"extract":[27],"the":[28,33,36,85,113,116,129,132],"latent":[29],"manifold":[30],"structure":[31],"of":[32,115,131,138],"entities":[34],"in":[35,68,84],"affinity":[37],"and":[39,48,60,76,88,108,111],"leverages":[40],"non-negative":[41],"least":[42],"squares":[43],"with":[44],"standard":[45],"simplex":[46],"constraints":[47],"power":[49],"iteration":[50],"derive":[53],"spectral":[54],"embeddings.":[55,125],"It":[56],"provides":[57],"an":[58],"effective":[59],"efficient":[61],"approach":[62,74],"combining":[64],"entity":[65],"representations":[66],"defined":[67],"different":[69,135],"Euclidean":[70],"spaces.":[71],"Specifically,":[72],"our":[73,139],"generates":[75],"imputes":[77],"reliable":[78],"embedding":[79,118],"vectors":[80],"low-frequency":[82],"words":[83],"benefits":[89],"downstream":[90],"language":[91,109],"tasks":[92],"that":[93],"depend":[94],"on":[95,102],"conduct":[99],"comprehensive":[100],"experiments":[101],"carefully":[104],"designed":[105],"classification":[106],"problem":[107],"modeling":[110],"demonstrate":[112],"superiority":[114],"enhanced":[117],"via":[119],"LSI":[120],"over":[121],"several":[122],"well-known":[123],"benchmark":[124],"also":[127],"confirm":[128],"consistency":[130],"results":[133],"under":[134],"parameter":[136],"settings":[137],"method.":[140]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2019-05-29T00:00:00"}