{"id":"https://openalex.org/W2133685191","doi":"https://doi.org/10.18653/v1/s15-2018","title":"FBK-HLT: A New Framework for Semantic Textual Similarity","display_name":"FBK-HLT: A New Framework for Semantic Textual Similarity","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2133685191","doi":"https://doi.org/10.18653/v1/s15-2018","mag":"2133685191"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s15-2018","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s15-2018","pdf_url":"https://www.aclweb.org/anthology/S15-2018.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 9th International Workshop on Semantic Evaluation (SemEval 2015)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/S15-2018.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015531707","display_name":"Ngoc Phuoc An Vo","orcid":"https://orcid.org/0000-0001-5646-5411"},"institutions":[{"id":"https://openalex.org/I33976269","display_name":"Xerox (France)","ror":"https://ror.org/033q0mv79","country_code":"FR","type":"company","lineage":["https://openalex.org/I33976269","https://openalex.org/I4210132870"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Ngoc Phuoc An Vo","raw_affiliation_strings":["Xerox (France), Saint-Denis, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xerox (France), Saint-Denis, France","institution_ids":["https://openalex.org/I33976269"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061447784","display_name":"Simone Magnolini","orcid":"https://orcid.org/0000-0003-0170-3472"},"institutions":[{"id":"https://openalex.org/I79940851","display_name":"University of Brescia","ror":"https://ror.org/02q2d2610","country_code":"IT","type":"education","lineage":["https://openalex.org/I79940851"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Simone Magnolini","raw_affiliation_strings":["University of Brescia, Brescia, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Brescia, Brescia, Italy","institution_ids":["https://openalex.org/I79940851"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034757155","display_name":"Octavian Popescu","orcid":"https://orcid.org/0000-0002-2597-7155"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Octavian Popescu","raw_affiliation_strings":["IBM, ,"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM, ,","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3355,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.86365118,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"102","last_page":"106"},"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":0.9998000264167786,"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/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7902958989143372},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.7611461877822876},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7216522097587585},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6644973754882812},{"id":"https://openalex.org/keywords/string","display_name":"String (physics)","score":0.656640887260437},{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.6411070823669434},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.6368902921676636},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5714219212532043},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5558286905288696},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4656110107898712},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.17170315980911255},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11131379008293152},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.060378074645996094}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7902958989143372},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7611461877822876},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7216522097587585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6644973754882812},{"id":"https://openalex.org/C157486923","wikidata":"https://www.wikidata.org/wiki/Q1376436","display_name":"String (physics)","level":2,"score":0.656640887260437},{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.6411070823669434},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.6368902921676636},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5714219212532043},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5558286905288696},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4656110107898712},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.17170315980911255},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11131379008293152},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.060378074645996094},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"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/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18653/v1/s15-2018","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s15-2018","pdf_url":"https://www.aclweb.org/anthology/S15-2018.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 9th International Workshop on Semantic Evaluation (SemEval 2015)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.726.820","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.726.820","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://alt.qcri.org/semeval2015/cdrom/pdf/SemEval018.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.18653/v1/s15-2018","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s15-2018","pdf_url":"https://www.aclweb.org/anthology/S15-2018.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 9th International Workshop on Semantic Evaluation (SemEval 2015)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.4399999976158142,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2133685191.pdf","grobid_xml":"https://content.openalex.org/works/W2133685191.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W1494404649","https://openalex.org/W1587871245","https://openalex.org/W1748393397","https://openalex.org/W1990061958","https://openalex.org/W1994790623","https://openalex.org/W2064587498","https://openalex.org/W2073265902","https://openalex.org/W2097606805","https://openalex.org/W2117805756","https://openalex.org/W2120779048","https://openalex.org/W2123301721","https://openalex.org/W2132069633","https://openalex.org/W2133458109","https://openalex.org/W2133990480","https://openalex.org/W2134168908","https://openalex.org/W2135875128","https://openalex.org/W2237235759","https://openalex.org/W2251861449","https://openalex.org/W2950225692","https://openalex.org/W2952846557"],"related_works":["https://openalex.org/W118347290","https://openalex.org/W2252122760","https://openalex.org/W78638240","https://openalex.org/W2910818272","https://openalex.org/W2809913388","https://openalex.org/W2471691717","https://openalex.org/W2752271464","https://openalex.org/W2104511424","https://openalex.org/W2161848918","https://openalex.org/W2606104864","https://openalex.org/W2251775411","https://openalex.org/W2251958591","https://openalex.org/W2251382073","https://openalex.org/W2602596682","https://openalex.org/W2798583685","https://openalex.org/W2147243590","https://openalex.org/W2753567482","https://openalex.org/W2270234620","https://openalex.org/W2111109675","https://openalex.org/W2753580119"],"abstract_inverted_index":{"This":[0],"paper":[1],"reports":[2],"the":[3,13,77,91],"description":[4],"and":[5,58,84],"performance":[6],"of":[7,49,64,72],"our":[8,62],"system,":[9],"FBK-HLT,":[10],"participating":[11],"in":[12,30,46],"SemEval":[14],"2015,":[15],"Task":[16],"#2":[17],"\"Semantic":[18],"Textual":[19],"Similarity\",":[20],"English":[21],"subtask.":[22],"We":[23,75],"submitted":[24],"three":[25],"runs":[26],"with":[27,41],"different":[28,47],"hypothesis":[29,63],"combining":[31],"typical":[32],"features":[33],"(lexical":[34],"similarity,":[35,37],"string":[36],"word":[38],"n-grams,":[39],"etc)":[40],"syntactic":[42,73],"structure":[43],"features,":[44],"resulting":[45],"sets":[48],"features.":[50],"The":[51],"results":[52],"evaluated":[53],"on":[54,80,94],"both":[55],"STS":[56,67,81,95],"2014":[57,82],"2015":[59,96],"datasets":[60,83],"prove":[61],"building":[65],"a":[66,86],"system":[68,79,93],"taking":[69],"into":[70],"consideration":[71],"information.":[74],"outperform":[76],"best":[78,92],"achieve":[85],"very":[87],"competitive":[88],"result":[89],"to":[90],"datasets.":[97]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}