{"id":"https://openalex.org/W2250426976","doi":"https://doi.org/10.3115/v1/d14-1046","title":"Automatic Domain Assignment for Word Sense Alignment","display_name":"Automatic Domain Assignment for Word Sense Alignment","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2250426976","doi":"https://doi.org/10.3115/v1/d14-1046","mag":"2250426976"},"language":"en","primary_location":{"id":"doi:10.3115/v1/d14-1046","is_oa":true,"landing_page_url":"http://doi.org/10.3115/v1/d14-1046","pdf_url":"https://doi.org/10.3115/v1/d14-1046","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3115/v1/d14-1046","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064384923","display_name":"Tommaso Caselli","orcid":"https://orcid.org/0000-0003-2936-0256"},"institutions":[{"id":"https://openalex.org/I4210161882","display_name":"Trento RISE (Italy)","ror":"https://ror.org/01nzc6q72","country_code":"IT","type":"company","lineage":["https://openalex.org/I4210161882"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Tommaso Caselli","raw_affiliation_strings":["Trento RISE"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Trento RISE","institution_ids":["https://openalex.org/I4210161882"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006685038","display_name":"Carlo Strapparava","orcid":"https://orcid.org/0000-0002-9365-0242"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carlo Strapparava","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"414","last_page":"418"},"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/T12353","display_name":"Lexicography and Language Studies","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1203","display_name":"Language and Linguistics"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.993399977684021,"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/wordnet","display_name":"WordNet","score":0.7968325614929199},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7751041650772095},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6234362125396729},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.582964301109314},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5807268619537354},{"id":"https://openalex.org/keywords/lexicographical-order","display_name":"Lexicographical order","score":0.5629040002822876},{"id":"https://openalex.org/keywords/word-sense-disambiguation","display_name":"Word-sense disambiguation","score":0.557933509349823},{"id":"https://openalex.org/keywords/lexicon","display_name":"Lexicon","score":0.5543814301490784},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5165842771530151},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5128443837165833},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.512155294418335},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.479621022939682},{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.44014236330986023},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4229412376880646},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13296544551849365},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.13051781058311462}],"concepts":[{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.7968325614929199},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7751041650772095},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6234362125396729},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.582964301109314},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5807268619537354},{"id":"https://openalex.org/C159254197","wikidata":"https://www.wikidata.org/wiki/Q1144915","display_name":"Lexicographical order","level":2,"score":0.5629040002822876},{"id":"https://openalex.org/C51646954","wikidata":"https://www.wikidata.org/wiki/Q48522","display_name":"Word-sense disambiguation","level":3,"score":0.557933509349823},{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.5543814301490784},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5165842771530151},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5128443837165833},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.512155294418335},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.479621022939682},{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.44014236330986023},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4229412376880646},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13296544551849365},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.13051781058311462},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","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/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3115/v1/d14-1046","is_oa":true,"landing_page_url":"http://doi.org/10.3115/v1/d14-1046","pdf_url":"https://doi.org/10.3115/v1/d14-1046","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.656.85","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.656.85","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://aclweb.org/anthology/D/D14/D14-1046.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.670.9309","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.670.9309","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://emnlp2014.org/papers/pdf/EMNLP2014046.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.3115/v1/d14-1046","is_oa":true,"landing_page_url":"http://doi.org/10.3115/v1/d14-1046","pdf_url":"https://doi.org/10.3115/v1/d14-1046","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.6899999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W22702538","https://openalex.org/W340380777","https://openalex.org/W799728889","https://openalex.org/W1480573250","https://openalex.org/W1526476048","https://openalex.org/W1560633476","https://openalex.org/W1580825123","https://openalex.org/W1750338658","https://openalex.org/W1928953731","https://openalex.org/W2038721957","https://openalex.org/W2079478118","https://openalex.org/W2120699290","https://openalex.org/W2130173309","https://openalex.org/W2135824681","https://openalex.org/W2159719802","https://openalex.org/W2166773381","https://openalex.org/W2186446900"],"related_works":["https://openalex.org/W1988325893","https://openalex.org/W2252023808","https://openalex.org/W3114765853","https://openalex.org/W189413142","https://openalex.org/W4385570727","https://openalex.org/W2480501668","https://openalex.org/W1561908597","https://openalex.org/W103065337","https://openalex.org/W2109049551","https://openalex.org/W2772864957"],"abstract_inverted_index":{"This":[0,76],"paper":[1],"reports":[2],"on":[3,13],"the":[4,26,39,61,83,86,90,93,99],"development":[5],"of":[6,29,35,51,56,85,92,101],"a":[7,14,36,54],"hy-brid":[8],"and":[9,23,73,98],"simple":[10],"method":[11],"based":[12],"machine":[15],"learning":[16],"classifier":[17],"(Naive":[18],"Bayes),":[19],"Word":[20],"Sense":[21],"Disambiguation":[22],"rules,":[24],"for":[25,95,104],"automatic":[27],"assignment":[28],"WordNet":[30],"Domains":[31],"to":[32,65,79],"nominal":[33],"entries":[34],"lexicographic":[37],"dictionary,":[38],"Senso":[40,74],"Comune":[41],"De":[42],"Mauro":[43],"Lexicon.":[44],"The":[45],"system":[46],"ob-tained":[47],"an":[48,80],"F1":[49],"score":[50],"0.58,":[52],"with":[53],"Precision":[55],"0.70.":[57],"We":[58],"further":[59],"used":[60],"automatically":[62],"as-signed":[63],"domains":[64],"filter":[66],"out":[67],"word":[68],"sense":[69,87,107],"align-ments":[70],"between":[71],"MultiWordNet":[72],"Co-mune.":[75],"has":[77],"led":[78],"improvement":[81],"in":[82],"quality":[84],"alignments":[88],"showing":[89],"validity":[91],"approach":[94],"domain":[96,102],"assign-ment":[97],"importance":[100],"informa-tion":[103],"achieving":[105],"good":[106],"alignments.":[108],"1":[109]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}