{"id":"https://openalex.org/W1965324211","doi":"https://doi.org/10.1145/2661829.2661955","title":"Semantic Compositionality in Tree Kernels","display_name":"Semantic Compositionality in Tree Kernels","publication_year":2014,"publication_date":"2014-11-03","ids":{"openalex":"https://openalex.org/W1965324211","doi":"https://doi.org/10.1145/2661829.2661955","mag":"1965324211"},"language":"en","primary_location":{"id":"doi:10.1145/2661829.2661955","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2661829.2661955","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management","raw_type":"proceedings-article"},"type":"conference-paper","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/A5058664091","display_name":"Paolo Annesi","orcid":null},"institutions":[{"id":"https://openalex.org/I116067653","display_name":"University of Rome Tor Vergata","ror":"https://ror.org/02p77k626","country_code":"IT","type":"education","lineage":["https://openalex.org/I116067653"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Paolo Annesi","raw_affiliation_strings":["University of Roma, Tor Vergata, Roma, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Roma, Tor Vergata, Roma, Italy","institution_ids":["https://openalex.org/I116067653"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041324718","display_name":"Danilo Croce","orcid":"https://orcid.org/0000-0001-9111-1950"},"institutions":[{"id":"https://openalex.org/I116067653","display_name":"University of Rome Tor Vergata","ror":"https://ror.org/02p77k626","country_code":"IT","type":"education","lineage":["https://openalex.org/I116067653"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Danilo Croce","raw_affiliation_strings":["University of Roma, Tor Vergata, Roma, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Roma, Tor Vergata, Roma, Italy","institution_ids":["https://openalex.org/I116067653"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083592532","display_name":"Roberto Basili","orcid":"https://orcid.org/0000-0001-5140-0694"},"institutions":[{"id":"https://openalex.org/I116067653","display_name":"University of Rome Tor Vergata","ror":"https://ror.org/02p77k626","country_code":"IT","type":"education","lineage":["https://openalex.org/I116067653"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Roberto Basili","raw_affiliation_strings":["University of Roma, Tor Vergata, Roma, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Roma, Tor Vergata, Roma, Italy","institution_ids":["https://openalex.org/I116067653"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I116067653"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1029","last_page":"1038"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","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/T10181","display_name":"Natural Language Processing Techniques","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/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9979000091552734,"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/principle-of-compositionality","display_name":"Principle of compositionality","score":0.8803200721740723},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8164740800857544},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7130903005599976},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6911420226097107},{"id":"https://openalex.org/keywords/tree-kernel","display_name":"Tree kernel","score":0.6910263299942017},{"id":"https://openalex.org/keywords/distributional-semantics","display_name":"Distributional semantics","score":0.534460186958313},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.4558481276035309},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.2373797595500946},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.1360672116279602},{"id":"https://openalex.org/keywords/kernel-embedding-of-distributions","display_name":"Kernel embedding of distributions","score":0.12319278717041016}],"concepts":[{"id":"https://openalex.org/C121375916","wikidata":"https://www.wikidata.org/wiki/Q936559","display_name":"Principle of compositionality","level":2,"score":0.8803200721740723},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8164740800857544},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7130903005599976},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6911420226097107},{"id":"https://openalex.org/C140417398","wikidata":"https://www.wikidata.org/wiki/Q16933942","display_name":"Tree kernel","level":5,"score":0.6910263299942017},{"id":"https://openalex.org/C2778828372","wikidata":"https://www.wikidata.org/wiki/Q5283209","display_name":"Distributional semantics","level":3,"score":0.534460186958313},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.4558481276035309},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.2373797595500946},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.1360672116279602},{"id":"https://openalex.org/C134517425","wikidata":"https://www.wikidata.org/wiki/Q16000131","display_name":"Kernel embedding of distributions","level":4,"score":0.12319278717041016}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2661829.2661955","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2661829.2661955","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:art.torvergata.it:2108/124223","is_oa":false,"landing_page_url":"http://hdl.handle.net/2108/124223","pdf_url":null,"source":{"id":"https://openalex.org/S4306400993","display_name":"Cineca Institutional Research Information System (Tor Vergata University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I116067653","host_organization_name":"University of Rome Tor Vergata","host_organization_lineage":["https://openalex.org/I116067653"],"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":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7400000095367432,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W97201605","https://openalex.org/W151785663","https://openalex.org/W1539150806","https://openalex.org/W1566018662","https://openalex.org/W1576213419","https://openalex.org/W1662133657","https://openalex.org/W1890485500","https://openalex.org/W1970409510","https://openalex.org/W1973942085","https://openalex.org/W1980776243","https://openalex.org/W1983578042","https://openalex.org/W1984052055","https://openalex.org/W1994383019","https://openalex.org/W2005181355","https://openalex.org/W2013494846","https://openalex.org/W2070246124","https://openalex.org/W2089150068","https://openalex.org/W2095589793","https://openalex.org/W2100693535","https://openalex.org/W2103305545","https://openalex.org/W2112706073","https://openalex.org/W2126704455","https://openalex.org/W2127713198","https://openalex.org/W2128870637","https://openalex.org/W2133280805","https://openalex.org/W2135011894","https://openalex.org/W2137607259","https://openalex.org/W2155870214","https://openalex.org/W2157860754","https://openalex.org/W2179987228","https://openalex.org/W2251471769","https://openalex.org/W2759083144","https://openalex.org/W2787381839","https://openalex.org/W2952064673","https://openalex.org/W2997185401","https://openalex.org/W2997914541","https://openalex.org/W3191219186","https://openalex.org/W6605815150","https://openalex.org/W6634338208","https://openalex.org/W6674298584","https://openalex.org/W6679091061","https://openalex.org/W6680585821"],"related_works":["https://openalex.org/W86971241","https://openalex.org/W1715304901","https://openalex.org/W2912764446","https://openalex.org/W2784926331","https://openalex.org/W4376653378","https://openalex.org/W84019336","https://openalex.org/W2170770969","https://openalex.org/W1847856012","https://openalex.org/W2572858686","https://openalex.org/W3112765659"],"abstract_inverted_index":{"Kernel-based":[0],"learning":[1],"has":[2,41],"been":[3,42,83,107],"largely":[4],"applied":[5],"to":[6,66,110,149,191],"semantic":[7,39,114],"textual":[8],"inference":[9],"tasks.":[10,33],"In":[11,135],"particular,":[12],"Tree":[13,145],"Kernels":[14],"(TKs)":[15],"are":[16,57],"crucial":[17],"in":[18,27,133],"the":[19,35,45,48,117,154,212],"modeling":[20],"of":[21,47,201],"syntactic":[22],"similarity":[23],"between":[24],"linguistic":[25,70],"instances":[26],"Question":[28,176],"Answering":[29],"or":[30,76,79],"Information":[31],"Extraction":[32],"At":[34],"same":[36],"time,":[37],"lexical":[38,55,90,104,162],"information":[40],"studied":[43,126],"through":[44],"adoption":[46],"so-called":[49],"Distributional":[50,99],"Semantics":[51,101],"(DS)":[52],"paradigm,":[53],"where":[54],"vectors":[56],"acquired":[58],"automatically":[59],"from":[60],"large":[61,199],"corpora.":[62],"Notice":[63],"how":[64],"methods":[65],"account":[67,130],"for":[68,122,131],"compositional":[69],"structures":[71,120],"(e.g.":[72,116],"grammatically":[73],"typed":[74],"bi-grams":[75],"complex":[77,167],"verb":[78],"noun":[80],"phrases)":[81],"have":[82,106],"proposed":[84,109,148,214],"recently":[85],"by":[86,158,211],"defining":[87],"algebras":[88],"on":[89,174],"vectors.":[91],"The":[92,170],"result":[93],"is":[94,147],"an":[95],"extended":[96],"paradigm":[97],"called":[98,141],"Compositional":[100],"(DCS).":[102],"Although":[103],"extensions":[105],"already":[108],"generalize":[111],"TKs":[112,127],"towards":[113],"phenomena":[115],"predicate":[118],"argument":[119],"as":[121],"role":[123],"labeling),":[124],"currently":[125],"do":[128],"not":[129],"compositionality,":[132],"general.":[134],"this":[136],"paper,":[137],"a":[138,175,198],"novel":[139],"kernel":[140,156,213],"Compositionally":[142],"Smoothed":[143],"Partial":[144],"Kernel":[146],"integrate":[150],"DCS":[151],"operators":[152],"into":[153],"tree":[155],"evaluation,":[157],"acting":[159],"both":[160],"over":[161],"leaves":[163],"and":[164,178,203],"non-terminal,":[165],"i.e.":[166],"compositional,":[168],"nodes.":[169],"empirical":[171],"results":[172],"obtained":[173],"Classification":[177],"Paraphrase":[179],"Identification":[180],"tasks":[181,206],"show":[182],"that":[183,197],"state-of-the-art":[184],"performances":[185],"can":[186,207],"be":[187,208],"achieved,":[188],"without":[189],"resorting":[190],"manual":[192],"feature":[193],"engineering,":[194],"thus":[195],"suggesting":[196],"set":[200],"Web":[202],"text":[204],"mining":[205],"handled":[209],"successfully":[210],"here.":[215]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}