{"id":"https://openalex.org/W2605137890","doi":"https://doi.org/10.18653/v1/w17-0913","title":"Story Cloze Ending Selection Baselines and Data Examination","display_name":"Story Cloze Ending Selection Baselines and Data Examination","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2605137890","doi":"https://doi.org/10.18653/v1/w17-0913","mag":"2605137890"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w17-0913","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w17-0913","pdf_url":"https://www.aclweb.org/anthology/W17-0913.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 2nd Workshop on Linking Models of Lexical,\n          Sentential and Discourse-level Semantics","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W17-0913.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052408504","display_name":"Todor Mihaylov","orcid":null},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Todor Mihaylov","raw_affiliation_strings":["Research Training Group AIPHES Institute for Computational Linguistics Heidelberg University"],"affiliations":[{"raw_affiliation_string":"Research Training Group AIPHES Institute for Computational Linguistics Heidelberg University","institution_ids":["https://openalex.org/I223822909"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023977688","display_name":"Anette Frank","orcid":"https://orcid.org/0000-0003-4706-9817"},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Anette Frank","raw_affiliation_strings":["Research Training Group AIPHES Institute for Computational Linguistics Heidelberg University"],"affiliations":[{"raw_affiliation_string":"Research Training Group AIPHES Institute for Computational Linguistics Heidelberg University","institution_ids":["https://openalex.org/I223822909"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5052408504"],"corresponding_institution_ids":["https://openalex.org/I223822909"],"apc_list":null,"apc_paid":null,"fwci":1.455,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.86404138,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"87","last_page":"92"},"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":0.9983000159263611,"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":0.9865999817848206,"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":0.78355872631073},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.71766197681427},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6405254006385803},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5795212388038635},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5359370112419128},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.507499635219574},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.4954608678817749},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.47698909044265747},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.4749695956707001},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.46496206521987915},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.4329741895198822},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.413249135017395},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.32354938983917236},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.15274116396903992},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.13361090421676636}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.78355872631073},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.71766197681427},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6405254006385803},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5795212388038635},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5359370112419128},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.507499635219574},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.4954608678817749},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.47698909044265747},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.4749695956707001},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.46496206521987915},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.4329741895198822},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.413249135017395},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32354938983917236},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.15274116396903992},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.13361090421676636},{"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/w17-0913","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w17-0913","pdf_url":"https://www.aclweb.org/anthology/W17-0913.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 2nd Workshop on Linking Models of Lexical,\n          Sentential and Discourse-level Semantics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/w17-0913","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w17-0913","pdf_url":"https://www.aclweb.org/anthology/W17-0913.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 2nd Workshop on Linking Models of Lexical,\n          Sentential and Discourse-level Semantics","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2962039251","display_name":null,"funder_award_id":"No. GRK","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G3424576390","display_name":null,"funder_award_id":"GRK 1994","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G481299621","display_name":null,"funder_award_id":"GRK 1994/1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2605137890.pdf","grobid_xml":"https://content.openalex.org/works/W2605137890.grobid-xml"},"referenced_works_count":19,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W2050482109","https://openalex.org/W2064675550","https://openalex.org/W2101234009","https://openalex.org/W2118585731","https://openalex.org/W2123442489","https://openalex.org/W2141599568","https://openalex.org/W2153045205","https://openalex.org/W2250539671","https://openalex.org/W2341557172","https://openalex.org/W2341790067","https://openalex.org/W2467646401","https://openalex.org/W2512735275","https://openalex.org/W2517226069","https://openalex.org/W2962958286","https://openalex.org/W2964121744","https://openalex.org/W2964150944","https://openalex.org/W4298149550"],"related_works":["https://openalex.org/W2081900870","https://openalex.org/W2037549926","https://openalex.org/W2188500270","https://openalex.org/W2303858293","https://openalex.org/W4286432911","https://openalex.org/W2966570129","https://openalex.org/W3099449837","https://openalex.org/W2774861092","https://openalex.org/W4301351852","https://openalex.org/W2622845166"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"two":[3],"supervised":[4],"baseline":[5],"systems":[6],"for":[7],"the":[8,48,51,54,73,78,88,97,111],"Story":[9],"Cloze":[10],"Test":[11],"Shared":[12],"Task":[13],"(Mostafazadeh":[14],"et":[15],"al.,":[16],"2016a).":[17],"We":[18,33],"first":[19],"build":[20],"a":[21,36,61],"classifier":[22],"using":[23,63],"features":[24,65,86],"based":[25,66],"on":[26,67],"word":[27,69],"embeddings":[28],"and":[29,53,77,90],"semantic":[30],"similarity":[31,85],"computation.":[32],"further":[34],"implement":[35],"neural":[37,98],"LSTM":[38],"system":[39],"with":[40,84],"different":[41],"encoding":[42],"strategies":[43],"that":[44,60],"try":[45],"to":[46],"model":[47,62,102],"relation":[49],"between":[50,87],"story":[52,75,89],"provided":[55],"endings.":[56],"Our":[57,100],"experiments":[58],"show":[59],"representation":[64],"average":[68],"embedding":[70],"vectors":[71],"over":[72],"given":[74],"words":[76],"candidate":[79,91],"ending":[80,92],"sentences":[81],"words,":[82],"joint":[83],"representations":[93],"performed":[94],"better":[95],"than":[96],"models.":[99],"best":[101],"achieves":[103],"an":[104],"accuracy":[105],"of":[106],"72.42,":[107],"ranking":[108],"3rd":[109],"in":[110],"official":[112],"evaluation.":[113]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":2}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
