{"id":"https://openalex.org/W2270550389","doi":"https://doi.org/10.1007/s10994-017-5634-8","title":"The mechanism of additive composition","display_name":"The mechanism of additive composition","publication_year":2017,"publication_date":"2017-04-03","ids":{"openalex":"https://openalex.org/W2270550389","doi":"https://doi.org/10.1007/s10994-017-5634-8","mag":"2270550389"},"language":"en","primary_location":{"id":"doi:10.1007/s10994-017-5634-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-017-5634-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-017-5634-8.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s10994-017-5634-8.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Ran Tian","orcid":"https://orcid.org/0000-0001-9146-2486"},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Ran Tian","raw_affiliation_strings":["Communication Science Laboratory, Tohoku University, 6-6-05, Sendai, Miyagi, 980-8579, Japan"],"raw_orcid":"https://orcid.org/0000-0001-9146-2486","affiliations":[{"raw_affiliation_string":"Communication Science Laboratory, Tohoku University, 6-6-05, Sendai, Miyagi, 980-8579, Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Naoaki Okazaki","orcid":null},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naoaki Okazaki","raw_affiliation_strings":["Communication Science Laboratory, Tohoku University, 6-6-05, Sendai, Miyagi, 980-8579, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication Science Laboratory, Tohoku University, 6-6-05, Sendai, Miyagi, 980-8579, Japan","institution_ids":["https://openalex.org/I201537933"]}]},{"author_position":"last","author":{"id":null,"display_name":"Kentaro Inui","orcid":null},"institutions":[{"id":"https://openalex.org/I201537933","display_name":"Tohoku University","ror":"https://ror.org/01dq60k83","country_code":"JP","type":"education","lineage":["https://openalex.org/I201537933"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kentaro Inui","raw_affiliation_strings":["Communication Science Laboratory, Tohoku University, 6-6-05, Sendai, Miyagi, 980-8579, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication Science Laboratory, Tohoku University, 6-6-05, Sendai, Miyagi, 980-8579, Japan","institution_ids":["https://openalex.org/I201537933"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I201537933"],"apc_list":{"value":2990,"currency":"USD","value_usd":2990},"apc_paid":{"value":2990,"currency":"USD","value_usd":2990},"fwci":0.9096,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.81219408,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"106","issue":"7","first_page":"1083","last_page":"1130"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.4327999949455261,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.4327999949455261,"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":0.19900000095367432,"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":0.08619999885559082,"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/composition","display_name":"Composition (language)","score":0.7444999814033508},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.578499972820282},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.5742999911308289},{"id":"https://openalex.org/keywords/collocation","display_name":"Collocation (remote sensing)","score":0.5375999808311462},{"id":"https://openalex.org/keywords/type","display_name":"Type (biology)","score":0.4950999915599823},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4814000129699707},{"id":"https://openalex.org/keywords/additive-model","display_name":"Additive model","score":0.4706999957561493},{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.46320000290870667},{"id":"https://openalex.org/keywords/decomposition","display_name":"Decomposition","score":0.4496000111103058}],"concepts":[{"id":"https://openalex.org/C40231798","wikidata":"https://www.wikidata.org/wiki/Q1333743","display_name":"Composition (language)","level":2,"score":0.7444999814033508},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.578499972820282},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.5742999911308289},{"id":"https://openalex.org/C80023036","wikidata":"https://www.wikidata.org/wiki/Q5147531","display_name":"Collocation (remote sensing)","level":2,"score":0.5375999808311462},{"id":"https://openalex.org/C2777299769","wikidata":"https://www.wikidata.org/wiki/Q3707858","display_name":"Type (biology)","level":2,"score":0.4950999915599823},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4814000129699707},{"id":"https://openalex.org/C203223496","wikidata":"https://www.wikidata.org/wiki/Q4681344","display_name":"Additive model","level":2,"score":0.4706999957561493},{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.46320000290870667},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4625000059604645},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.4496000111103058},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.40959998965263367},{"id":"https://openalex.org/C121375916","wikidata":"https://www.wikidata.org/wiki/Q936559","display_name":"Principle of compositionality","level":2,"score":0.4023999869823456},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3961000144481659},{"id":"https://openalex.org/C13336665","wikidata":"https://www.wikidata.org/wiki/Q125977","display_name":"Vector space","level":2,"score":0.38260000944137573},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.3675000071525574},{"id":"https://openalex.org/C38803922","wikidata":"https://www.wikidata.org/wiki/Q95745348","display_name":"Additive function","level":2,"score":0.35260000824928284},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3089999854564667},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.290800005197525},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2897000014781952},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C2778220771","wikidata":"https://www.wikidata.org/wiki/Q1522579","display_name":"Substitution (logic)","level":2,"score":0.2833999991416931},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27489998936653137},{"id":"https://openalex.org/C88871306","wikidata":"https://www.wikidata.org/wiki/Q7208287","display_name":"Point process","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2615000009536743},{"id":"https://openalex.org/C2781147490","wikidata":"https://www.wikidata.org/wiki/Q5156808","display_name":"Compositional data","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.2574000060558319},{"id":"https://openalex.org/C194648359","wikidata":"https://www.wikidata.org/wiki/Q3318054","display_name":"Generalized additive model","level":2,"score":0.25619998574256897},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.25200000405311584}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s10994-017-5634-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-017-5634-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-017-5634-8.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1511.08407","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1511.08407","pdf_url":"https://arxiv.org/pdf/1511.08407","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"doi:10.1007/s10994-017-5634-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10994-017-5634-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10994-017-5634-8.pdf","source":{"id":"https://openalex.org/S62148650","display_name":"Machine Learning","issn_l":"0885-6125","issn":["0885-6125","1573-0565"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Machine Learning","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320338075","display_name":"Core Research for Evolutional Science and Technology","ror":"https://ror.org/00097mb19"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2270550389.pdf","grobid_xml":"https://content.openalex.org/works/W2270550389.grobid-xml"},"referenced_works_count":64,"referenced_works":["https://openalex.org/W97201605","https://openalex.org/W242422246","https://openalex.org/W1484288670","https://openalex.org/W1486777056","https://openalex.org/W1500002472","https://openalex.org/W1507719567","https://openalex.org/W1530392788","https://openalex.org/W1549334072","https://openalex.org/W1593045043","https://openalex.org/W1608322251","https://openalex.org/W1615991656","https://openalex.org/W1662133657","https://openalex.org/W1889268436","https://openalex.org/W1983578042","https://openalex.org/W1984052055","https://openalex.org/W2000042664","https://openalex.org/W2038976544","https://openalex.org/W2076118331","https://openalex.org/W2087309226","https://openalex.org/W2089150068","https://openalex.org/W2091297126","https://openalex.org/W2095958485","https://openalex.org/W2100693535","https://openalex.org/W2103305545","https://openalex.org/W2103318667","https://openalex.org/W2107484888","https://openalex.org/W2117756735","https://openalex.org/W2125031621","https://openalex.org/W2125786288","https://openalex.org/W2128713194","https://openalex.org/W2138204974","https://openalex.org/W2141599568","https://openalex.org/W2146502635","https://openalex.org/W2153579005","https://openalex.org/W2154099718","https://openalex.org/W2156909104","https://openalex.org/W2158139315","https://openalex.org/W2160943512","https://openalex.org/W2165496929","https://openalex.org/W2174706414","https://openalex.org/W2250189634","https://openalex.org/W2250275510","https://openalex.org/W2250453281","https://openalex.org/W2250473257","https://openalex.org/W2250508463","https://openalex.org/W2250716442","https://openalex.org/W2250962466","https://openalex.org/W2251047310","https://openalex.org/W2251471769","https://openalex.org/W2251642297","https://openalex.org/W2415801397","https://openalex.org/W2510102199","https://openalex.org/W2510403706","https://openalex.org/W2518186251","https://openalex.org/W2882319491","https://openalex.org/W3161552047","https://openalex.org/W6629970145","https://openalex.org/W6632662926","https://openalex.org/W6634133269","https://openalex.org/W6641017118","https://openalex.org/W6665831563","https://openalex.org/W6680585821","https://openalex.org/W6683738474","https://openalex.org/W6691431627"],"related_works":[],"abstract_inverted_index":{"Additive":[0],"composition":[1,110,154,196],"(Foltz":[2],"et":[3],"al.":[4],"in":[5,14,23,84],"Discourse":[6],"Process":[7],"15:285\u2013307,":[8],"1998":[9],";":[10,19],"Landauer":[11],"and":[12,21,132,164,201],"Dumais":[13],"Psychol":[15],"Rev":[16],"104(2):211,":[17],"1997":[18],"Mitchell":[20],"Lapata":[22],"Cognit":[24],"Sci":[25],"34(8):1388\u20131429,":[26],"2010":[27],")":[28],"is":[29,65,82,143],"a":[30,74,146,156,179,183,187],"widely":[31],"used":[32],"method":[33],"for":[34,58,159],"computing":[35],"meanings":[36,161],"of":[37,43,46,61,78,86,124,162,174,190],"phrases,":[38,163],"which":[39,64],"takes":[40],"the":[41,47,59,66,92,102,115,141],"average":[42],"vector":[44,191],"representations":[45,192],"constituent":[48],"words.":[49],"In":[50],"this":[51],"article,":[52],"we":[53,89],"prove":[54,90],"an":[55,112,138],"upper":[56],"bound":[57,81],"bias":[60],"additive":[62,109,153,169,195],"composition,":[63],"first":[67],"theoretical":[68],"analysis":[69],"on":[70,122],"compositional":[71],"frameworks":[72],"from":[73,137,145],"machine":[75],"learning":[76],"point":[77],"view.":[79],"The":[80,150],"written":[83],"terms":[85],"collocation":[87],"strength;":[88],"that":[91,128,140,181],"more":[93,103],"exclusively":[94],"two":[95],"successive":[96],"words":[97],"tend":[98],"to":[99,114,167,193,198,206],"occur":[100],"together,":[101],"accurate":[104],"one":[105],"can":[106,133],"guarantee":[107],"their":[108],"as":[111,155],"approximation":[113],"natural":[116,125],"phrase":[117],"vector.":[118],"Our":[119],"proof":[120],"relies":[121],"properties":[123],"language":[126],"data":[127,142],"are":[129],"empirically":[130],"verified,":[131],"be":[134],"theoretically":[135],"derived":[136],"assumption":[139],"generated":[144],"Hierarchical":[147],"Pitman\u2013Yor":[148],"Process.":[149],"theory":[151],"endorses":[152],"reasonable":[157],"operation":[158],"calculating":[160],"suggests":[165],"ways":[166],"improve":[168],"compositionality,":[170],"including:":[171],"transforming":[172],"entries":[173],"distributional":[175],"word":[176,199,208],"vectors":[177],"by":[178],"function":[180],"meets":[182],"specific":[184],"condition,":[185],"constructing":[186],"novel":[188],"type":[189],"make":[194],"sensitive":[197],"order,":[200],"utilizing":[202],"singular":[203],"value":[204],"decomposition":[205],"train":[207],"vectors.":[209]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2016-06-24T00:00:00"}