{"id":"https://openalex.org/W2513276162","doi":"https://doi.org/10.18653/v1/w16-1626","title":"Learning Word Importance with the Neural Bag-of-Words Model","display_name":"Learning Word Importance with the Neural Bag-of-Words Model","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2513276162","doi":"https://doi.org/10.18653/v1/w16-1626","mag":"2513276162"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w16-1626","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w16-1626","pdf_url":"https://doi.org/10.18653/v1/w16-1626","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st Workshop on Representation Learning for NLP","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.18653/v1/w16-1626","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023803850","display_name":"Imran Sheikh","orcid":"https://orcid.org/0000-0001-5041-7398"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Imran Sheikh","raw_affiliation_strings":["MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication (France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication (France)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073463405","display_name":"Irina Illina","orcid":"https://orcid.org/0000-0003-2598-4643"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Irina Illina","raw_affiliation_strings":["MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication (France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication (France)","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046546502","display_name":"Dominique Fohr","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dominique Fohr","raw_affiliation_strings":["MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication (France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication (France)","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050508708","display_name":"Georges Linar\u00e8s","orcid":"https://orcid.org/0000-0001-8049-9056"},"institutions":[{"id":"https://openalex.org/I4210119991","display_name":"Laboratoire Informatique d'Avignon","ror":"https://ror.org/02n399288","country_code":"FR","type":"facility","lineage":["https://openalex.org/I198415970","https://openalex.org/I4210119991"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Georges Linar\u00e8s","raw_affiliation_strings":["LIA - Laboratoire Informatique d'Avignon (339 Chemin des Meinajaries Agroparc BP 1228 84911 Avignon cedex 9 - France)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LIA - Laboratoire Informatique d'Avignon (339 Chemin des Meinajaries Agroparc BP 1228 84911 Avignon cedex 9 - France)","institution_ids":["https://openalex.org/I4210119991"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5023803850"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.9754,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.94470299,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"222","last_page":"229"},"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":0.9998000264167786,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9991000294685364,"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","display_name":"Word (group theory)","score":0.8138911724090576},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8004634380340576},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7192511558532715},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6061168909072876},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5924432277679443},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5726639628410339},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3287118673324585},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11922401189804077}],"concepts":[{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.8138911724090576},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8004634380340576},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7192511558532715},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6061168909072876},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5924432277679443},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5726639628410339},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3287118673324585},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11922401189804077},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"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:10.18653/v1/w16-1626","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w16-1626","pdf_url":"https://doi.org/10.18653/v1/w16-1626","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st Workshop on Representation Learning for NLP","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/w16-1626","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w16-1626","pdf_url":"https://doi.org/10.18653/v1/w16-1626","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 1st Workshop on Representation Learning for NLP","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7099999785423279,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W6908809","https://openalex.org/W1487016832","https://openalex.org/W1514535095","https://openalex.org/W1614298861","https://openalex.org/W1832693441","https://openalex.org/W1855892484","https://openalex.org/W2025954161","https://openalex.org/W2105745022","https://openalex.org/W2109634664","https://openalex.org/W2113459411","https://openalex.org/W2114960120","https://openalex.org/W2117130368","https://openalex.org/W2120615054","https://openalex.org/W2125109223","https://openalex.org/W2125573226","https://openalex.org/W2131744502","https://openalex.org/W2141599568","https://openalex.org/W2154359981","https://openalex.org/W2158139315","https://openalex.org/W2163455955","https://openalex.org/W2187089797","https://openalex.org/W2250473257","https://openalex.org/W2250539671","https://openalex.org/W2251008987","https://openalex.org/W2251103205","https://openalex.org/W2251124635","https://openalex.org/W2251803266","https://openalex.org/W2251830157","https://openalex.org/W2251939518","https://openalex.org/W2295000399","https://openalex.org/W2950178297","https://openalex.org/W2963042536","https://openalex.org/W2963083845","https://openalex.org/W2963355447","https://openalex.org/W2963921497","https://openalex.org/W2964308564","https://openalex.org/W2964321678","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W1569283511","https://openalex.org/W4236193183","https://openalex.org/W2053866214","https://openalex.org/W2607505004","https://openalex.org/W2231795205","https://openalex.org/W2523632547","https://openalex.org/W2143882141","https://openalex.org/W4391165988","https://openalex.org/W1586294928","https://openalex.org/W2296205523"],"abstract_inverted_index":{"The":[0,53],"Neural":[1],"Bag-of-Words":[2],"(NBOW)":[3],"model\r\nperforms":[4],"classification":[5,25,73],"with":[6,45],"an":[7,15],"average":[8],"of\r\nthe":[9],"input":[10],"word":[11,21,51,54,66,101,108],"vectors":[12,22],"and":[13],"achieves":[14],"impressive\r\nperformance.":[16],"While":[17],"the":[18,65],"NBOW\r\nmodel":[19],"learns":[20,81],"targeted":[23],"for\r\nthe":[24],"task":[26,49,87],"it":[27],"does":[28],"not":[29],"explicitly\r\nmodel":[30],"which":[31],"words":[32],"are":[33,104],"important":[34],"for\r\ngiven":[35],"task.":[36],"In":[37],"this":[38,46],"paper":[39],"we":[40,75],"propose":[41],"an\r\nimproved":[42],"NBOW":[43],"model":[44,80,89],"ability\r\nto":[47],"learn":[48],"specific":[50],"importance\r\nweights.":[52],"importance":[55,83,102],"weights\r\nare":[56],"learned":[57],"by":[58],"introducing":[59],"a":[60,85,114],"new":[61],"weighted\r\nsum":[62],"composition":[63],"of":[64],"vectors.\r\nWith":[67],"experiments":[68],"on":[69],"standard":[70],"topic":[71],"and\r\nsentiment":[72],"tasks,":[74],"show\r\nthat":[76],"(a)":[77],"our":[78],"proposed":[79],"meaningful\r\nword":[82],"for":[84],"given":[86],"(b)\r\nour":[88],"gives":[90],"best":[91],"accuracies":[92],"among":[93],"the\r\nBOW":[94],"approaches.":[95],"We":[96],"also":[97],"show":[98],"that":[99],"the\r\nlearned":[100],"weights":[103,109],"comparable\r\nto":[105],"tf-idf":[106],"based":[107],"when\r\nused":[110],"as":[111],"features":[112],"in":[113],"BOWSVM":[115],"classifier.":[116]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":4},{"year":2016,"cited_by_count":1}],"updated_date":"2026-05-19T21:40:30.786675","created_date":"2025-10-10T00:00:00"}
