{"id":"https://openalex.org/W2111597839","doi":"https://doi.org/10.1145/2663792.2663793","title":"A Study on the CBOW Model's Overfitting and Stability","display_name":"A Study on the CBOW Model's Overfitting and Stability","publication_year":2014,"publication_date":"2014-11-03","ids":{"openalex":"https://openalex.org/W2111597839","doi":"https://doi.org/10.1145/2663792.2663793","mag":"2111597839"},"language":"en","primary_location":{"id":"doi:10.1145/2663792.2663793","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2663792.2663793","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Workshop on Web-scale Knowledge Representation Retrieval & Reasoning","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/A5110162441","display_name":"Qun Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qun Luo","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001956210","display_name":"Weiran Xu","orcid":"https://orcid.org/0000-0002-7988-080X"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiran Xu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100445470","display_name":"Jun Guo","orcid":"https://orcid.org/0000-0001-9045-1339"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Guo","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5110162441"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.818,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.81489046,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"9","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998000264167786,"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":0.9998000264167786,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9886999726295471,"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":0.7654510736465454},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6791215538978577},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.6708900928497314},{"id":"https://openalex.org/keywords/bag-of-words-model","display_name":"Bag-of-words model","score":0.6532178521156311},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6158669590950012},{"id":"https://openalex.org/keywords/spamming","display_name":"Spamming","score":0.5196167826652527},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.49431610107421875},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.45508649945259094},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4389406740665436},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.156415194272995},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.10481992363929749}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7654510736465454},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6791215538978577},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.6708900928497314},{"id":"https://openalex.org/C13672336","wikidata":"https://www.wikidata.org/wiki/Q3460803","display_name":"Bag-of-words model","level":2,"score":0.6532178521156311},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6158669590950012},{"id":"https://openalex.org/C158955206","wikidata":"https://www.wikidata.org/wiki/Q83058","display_name":"Spamming","level":3,"score":0.5196167826652527},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.49431610107421875},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.45508649945259094},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4389406740665436},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.156415194272995},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.10481992363929749},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2663792.2663793","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2663792.2663793","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Workshop on Web-scale Knowledge Representation Retrieval & Reasoning","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1970689298","https://openalex.org/W1989149221","https://openalex.org/W2067438047","https://openalex.org/W2091812280","https://openalex.org/W2113459411","https://openalex.org/W2117130368","https://openalex.org/W2120779048","https://openalex.org/W2131462252","https://openalex.org/W2141599568","https://openalex.org/W2158139315","https://openalex.org/W2158899491","https://openalex.org/W2164019165","https://openalex.org/W2170682101","https://openalex.org/W2185726469","https://openalex.org/W2251012068","https://openalex.org/W2950577311","https://openalex.org/W2997617958","https://openalex.org/W2998704965","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W1987732684","https://openalex.org/W4362597605","https://openalex.org/W2393964553","https://openalex.org/W2943490005","https://openalex.org/W2003072179","https://openalex.org/W3036941175","https://openalex.org/W4292167554","https://openalex.org/W3138737920","https://openalex.org/W3805906","https://openalex.org/W2570094154"],"abstract_inverted_index":{"Word":[0],"vectors":[1,27],"are":[2],"distributed":[3],"representations":[4],"of":[5,71,92],"word":[6,17,26,55,78,93,102,112],"features.":[7],"Continuous":[8],"Bag-of-Words":[9],"Model(CBOW)":[10],"is":[11,33],"a":[12],"state-of-the-art":[13],"model":[14,74],"for":[15,23,81,101,111],"learning":[16,24],"vectors,":[18,94],"yet":[19],"can":[20,52],"be":[21,36],"ameliorated":[22],"better":[25,54],"because":[28],"we":[29,60],"find":[30],"that":[31,50],"CBOW":[32,51,73,83],"vulnerable":[34],"to":[35,44,67,99,109,117],"overfitted":[37],"and":[38,75,104],"unstable.":[39],"We":[40],"use":[41],"two":[42,47],"methods":[43,87],"solve":[45],"these":[46],"problems":[48],"so":[49],"learn":[53],"vectors.":[56],"In":[57],"this":[58],"study,":[59],"add":[61],"the":[62,68,72,82,90],"regularized":[63],"structure":[64],"risk":[65],"summation":[66],"objective":[69],"function":[70],"propose":[76],"inverse":[77],"frequency":[79],"encoding":[80],"model.":[84],"Our":[85],"proposed":[86],"substantially":[88],"improve":[89],"quality":[91],"boosting":[95],"r":[96],"from":[97,107],"0.638":[98],"0.696":[100],"relatedness":[103,115],"total":[105],"accuracy":[106],"30.80%":[108],"38.43%":[110],"pairs":[113],"relationship":[114],"regarding":[116],"52":[118],"million":[119],"training":[120],"words":[121],"with":[122],"200":[123],"dimensionality.":[124]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}