{"id":"https://openalex.org/W2163929207","doi":"https://doi.org/10.18653/v1/s15-2020","title":"SemantiKLUE: Semantic Textual Similarity with Maximum Weight Matching","display_name":"SemantiKLUE: Semantic Textual Similarity with Maximum Weight Matching","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2163929207","doi":"https://doi.org/10.18653/v1/s15-2020","mag":"2163929207"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s15-2020","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s15-2020","pdf_url":"https://www.aclweb.org/anthology/S15-2020.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/S15-2020.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062666267","display_name":"Nataliia Plotnikova","orcid":"https://orcid.org/0000-0001-9719-6238"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Nataliia Plotnikova","raw_affiliation_strings":["Friedrich-Alexander-Universitt Erlangen-Nrnberg (FAU) Professur fr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany","Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU) Professur f\u00fcr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universitt Erlangen-Nrnberg (FAU) Professur fr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]},{"raw_affiliation_string":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU) Professur f\u00fcr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034488796","display_name":"Gabriella Lapesa","orcid":"https://orcid.org/0000-0002-4418-3609"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gabriella Lapesa","raw_affiliation_strings":["Friedrich-Alexander-Universitt Erlangen-Nrnberg (FAU) Professur fr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany","Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU) Professur f\u00fcr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universitt Erlangen-Nrnberg (FAU) Professur fr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]},{"raw_affiliation_string":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU) Professur f\u00fcr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5029476870","display_name":"Thomas Proisl","orcid":"https://orcid.org/0000-0001-5513-9075"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Proisl","raw_affiliation_strings":["Friedrich-Alexander-Universitt Erlangen-Nrnberg (FAU) Professur fr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany","Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU) Professur f\u00fcr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universitt Erlangen-Nrnberg (FAU) Professur fr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]},{"raw_affiliation_string":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU) Professur f\u00fcr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016661742","display_name":"Stefan Evert","orcid":"https://orcid.org/0000-0002-4192-2437"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Stefan Evert","raw_affiliation_strings":["Friedrich-Alexander-Universitt Erlangen-Nrnberg (FAU) Professur fr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany","Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU) Professur f\u00fcr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universitt Erlangen-Nrnberg (FAU) Professur fr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]},{"raw_affiliation_string":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg (FAU) Professur f\u00fcr Korpuslinguistik Bismarckstr. 6, 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5062666267"],"corresponding_institution_ids":["https://openalex.org/I181369854"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05437664,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"111","last_page":"116"},"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/T13629","display_name":"Text Readability and Simplification","score":0.9975000023841858,"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/semeval","display_name":"SemEval","score":0.9497320652008057},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7845345139503479},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.7071748375892639},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6889591217041016},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6567707061767578},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6514252424240112},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6218082904815674},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6141994595527649},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6100154519081116},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.5655696392059326},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.5555287003517151},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.54198157787323},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3240693211555481},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12349510192871094},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10828623175621033}],"concepts":[{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.9497320652008057},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7845345139503479},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.7071748375892639},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6889591217041016},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6567707061767578},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6514252424240112},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6218082904815674},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6141994595527649},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6100154519081116},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.5655696392059326},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.5555287003517151},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.54198157787323},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3240693211555481},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12349510192871094},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10828623175621033},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/s15-2020","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s15-2020","pdf_url":"https://www.aclweb.org/anthology/S15-2020.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"}],"best_oa_location":{"id":"doi:10.18653/v1/s15-2020","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s15-2020","pdf_url":"https://www.aclweb.org/anthology/S15-2020.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":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2163929207.pdf","grobid_xml":"https://content.openalex.org/works/W2163929207.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W1489181569","https://openalex.org/W1647729745","https://openalex.org/W2101234009","https://openalex.org/W2106279089","https://openalex.org/W2121129054","https://openalex.org/W2130337399","https://openalex.org/W2133458109","https://openalex.org/W2155870214","https://openalex.org/W2251291469","https://openalex.org/W2252238828","https://openalex.org/W2534712034"],"related_works":["https://openalex.org/W3116116498","https://openalex.org/W3029012650","https://openalex.org/W2752041471","https://openalex.org/W78638240","https://openalex.org/W2252122760","https://openalex.org/W2105461184","https://openalex.org/W2114797768","https://openalex.org/W2380654781","https://openalex.org/W2176214140","https://openalex.org/W2516873349"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"the":[3,30,46,57,85,102],"SemantiKLUE":[4,107],"system":[5,7,58],"The":[6],"was":[8],"developed":[9],"for":[10,14,29,105],"SemEval-2013":[11],"and":[12,22],"extended":[13],"SemEval-2014,":[15],"where":[16],"it":[17],"participated":[18],"in":[19,77],"three":[20],"tasks":[21],"ranked":[23],"13th":[24],"out":[25,40,64],"of":[26,41,48,65,72,83,93,101],"38":[27],"submissions":[28],"English":[31],"STS":[32,87,110],"task.":[33],"While":[34],"this":[35],"year's":[36],"submission":[37],"ranks":[38],"46th":[39],"73,":[42],"further":[43],"experiments":[44,76],"on":[45,98],"selection":[47,75],"training":[49,74],"data":[50],"led":[51],"to":[52],"notable":[53],"improvements":[54],"showing":[55],"that":[56],"could":[59],"have":[60],"achieved":[61],"rank":[62],"22":[63],"73.":[66],"We":[67],"report":[68],"a":[69,94,99],"detailed":[70],"analysis":[71,96],"those":[73],"which":[78,106],"we":[79],"tested":[80],"different":[81],"combinations":[82],"all":[84],"available":[86],"datasets,":[88],"as":[89,91],"well":[90],"results":[92],"qualitative":[95],"conducted":[97],"sample":[100],"sentence":[103],"pairs":[104],"gave":[108],"wrong":[109],"predictions.":[111]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}