{"id":"https://openalex.org/W2098591950","doi":"https://doi.org/10.3115/v1/s14-1013","title":"Compositional Distributional Semantics Models in Chunk-based Smoothed Tree Kernels","display_name":"Compositional Distributional Semantics Models in Chunk-based Smoothed Tree Kernels","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2098591950","doi":"https://doi.org/10.3115/v1/s14-1013","mag":"2098591950"},"language":"en","primary_location":{"id":"doi:10.3115/v1/s14-1013","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/s14-1013","pdf_url":"https://aclanthology.org/S14-1013.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Third Joint Conference on Lexical and Computational Semantics (*SEM 2014)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/S14-1013.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002238661","display_name":"Nghia The Pham","orcid":null},"institutions":[{"id":"https://openalex.org/I193223587","display_name":"University of Trento","ror":"https://ror.org/05trd4x28","country_code":"IT","type":"education","lineage":["https://openalex.org/I193223587"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Nghia The Pham","raw_affiliation_strings":["University of Trento"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Trento","institution_ids":["https://openalex.org/I193223587"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086820378","display_name":"Lorenzo Ferrone","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":"Lorenzo Ferrone","raw_affiliation_strings":["University of Rome \"Tor Vergata\"","University of Rome Tor Vergata, Rome, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Rome \"Tor Vergata\"","institution_ids":["https://openalex.org/I116067653"]},{"raw_affiliation_string":"University of Rome Tor Vergata, Rome, Italy","institution_ids":["https://openalex.org/I116067653"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029654514","display_name":"Fabio Massimo Zanzotto","orcid":"https://orcid.org/0000-0002-7301-3596"},"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":"Fabio Massimo Zanzotto","raw_affiliation_strings":["University of Rome \"Tor Vergata\"","University of Rome Tor Vergata"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Rome \"Tor Vergata\"","institution_ids":["https://openalex.org/I116067653"]},{"raw_affiliation_string":"University of Rome Tor Vergata","institution_ids":["https://openalex.org/I116067653"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11034102,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"93","last_page":"98"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T10181","display_name":"Natural Language Processing Techniques","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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9950000047683716,"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":0.8475401401519775},{"id":"https://openalex.org/keywords/principle-of-compositionality","display_name":"Principle of compositionality","score":0.6926535367965698},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6908919811248779},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.6326293349266052},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.623529314994812},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6009067296981812},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5578867197036743},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5509339570999146},{"id":"https://openalex.org/keywords/textual-entailment","display_name":"Textual entailment","score":0.5291317701339722},{"id":"https://openalex.org/keywords/distributional-semantics","display_name":"Distributional semantics","score":0.5017848014831543},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.47679567337036133},{"id":"https://openalex.org/keywords/logical-consequence","display_name":"Logical consequence","score":0.45737361907958984},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.19789093732833862},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.19229081273078918},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10095882415771484}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8475401401519775},{"id":"https://openalex.org/C121375916","wikidata":"https://www.wikidata.org/wiki/Q936559","display_name":"Principle of compositionality","level":2,"score":0.6926535367965698},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6908919811248779},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.6326293349266052},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.623529314994812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6009067296981812},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5578867197036743},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5509339570999146},{"id":"https://openalex.org/C95318506","wikidata":"https://www.wikidata.org/wiki/Q6588467","display_name":"Textual entailment","level":3,"score":0.5291317701339722},{"id":"https://openalex.org/C2778828372","wikidata":"https://www.wikidata.org/wiki/Q5283209","display_name":"Distributional semantics","level":3,"score":0.5017848014831543},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.47679567337036133},{"id":"https://openalex.org/C134752490","wikidata":"https://www.wikidata.org/wiki/Q374182","display_name":"Logical consequence","level":2,"score":0.45737361907958984},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.19789093732833862},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.19229081273078918},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10095882415771484},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3115/v1/s14-1013","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/s14-1013","pdf_url":"https://aclanthology.org/S14-1013.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Third Joint Conference on Lexical and Computational Semantics (*SEM 2014)","raw_type":"proceedings-article"},{"id":"pmh:oai:art.torvergata.it:2108/101850","is_oa":true,"landing_page_url":"http://hdl.handle.net/2108/101850","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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"doi:10.3115/v1/s14-1013","is_oa":true,"landing_page_url":"https://doi.org/10.3115/v1/s14-1013","pdf_url":"https://aclanthology.org/S14-1013.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Third Joint Conference on Lexical and Computational Semantics (*SEM 2014)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.49000000953674316,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2098591950.pdf","grobid_xml":"https://content.openalex.org/works/W2098591950.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W151785663","https://openalex.org/W1484288670","https://openalex.org/W1499641710","https://openalex.org/W1576213419","https://openalex.org/W1608322251","https://openalex.org/W1990524510","https://openalex.org/W2100693535","https://openalex.org/W2101871539","https://openalex.org/W2115736534","https://openalex.org/W2130158090","https://openalex.org/W2131297983","https://openalex.org/W2137607259","https://openalex.org/W2154474435","https://openalex.org/W2251471769","https://openalex.org/W4211148418"],"related_works":["https://openalex.org/W2169644218","https://openalex.org/W12963412","https://openalex.org/W2250460949","https://openalex.org/W3158371345","https://openalex.org/W3141423438","https://openalex.org/W2071098659","https://openalex.org/W2962876005","https://openalex.org/W2478536981","https://openalex.org/W4302433841","https://openalex.org/W3130391454"],"abstract_inverted_index":{"The":[0],"field":[1],"of":[2,18,61],"compositional":[3,63,86],"distributional":[4,16,87],"semantics":[5],"has":[6],"proposed":[7],"very":[8],"interesting":[9],"and":[10,97],"reliable":[11],"models":[12,22,64,89],"for":[13,65],"accounting":[14],"the":[15,27,42,53,59,71,94],"meaning":[17],"simple":[19,66],"phrases.":[20,67],"These":[21],"however":[23],"tend":[24],"to":[25,34,51],"disregard":[26],"syntactic":[28,54,101],"structures":[29,55],"when":[30],"they":[31],"are":[32],"applied":[33,92],"larger":[35],"sentences.":[36],"In":[37],"this":[38],"paper":[39],"we":[40],"propose":[41],"chunk-based":[43],"smoothed":[44],"tree":[45,102],"kernels":[46],"(CSTKs)":[47],"as":[48,56,58],"a":[49],"way":[50],"exploit":[52],"well":[57],"reliability":[60],"these":[62],"We":[68],"experiment":[69],"with":[70],"recognizing":[72],"textual":[73],"entailment":[74],"datasets.":[75],"Our":[76],"experiments":[77],"show":[78],"that":[79],"our":[80],"CSTKs":[81],"perform":[82],"better":[83,99],"than":[84,100],"basic":[85],"semantic":[88],"(CDSMs)":[90],"recursively":[91],"at":[93],"sentence":[95],"level,":[96],"also":[98],"kernels.":[103]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}