{"id":"https://openalex.org/W2129272839","doi":null,"title":"Unsupervised Discovery of Event Scenarios from Texts","display_name":"Unsupervised Discovery of Event Scenarios from Texts","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W2129272839","mag":"2129272839"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.662.6348","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.662.6348","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.aaai.org/Papers/FLAIRS/2008/FLAIRS08-038.pdf","raw_type":"text"},"volume":null,"type":"article","indexed_in":[],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5054117089","display_name":"Cosmin Adrian Bejan","orcid":"https://orcid.org/0000-0001-5107-0584","observed_orcids":["https://orcid.org/0000-0001-5107-0584"]},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Cosmin A. Bejan","raw_affiliation_strings":["University of Texas at Dallas"],"raw_orcid":"https://orcid.org/0000-0001-5107-0584","affiliations":[{"raw_affiliation_string":"University of Texas at Dallas","institution_ids":["https://openalex.org/I162577319"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5054117089"],"corresponding_institution_ids":["https://openalex.org/I162577319"],"apc_list":null,"apc_paid":null,"fwci":2.6434,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.9098096,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"124","last_page":"129"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.6689000129699707,"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":0.6689000129699707,"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":0.3005000054836273,"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.00570000009611249,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/event-scenarios","display_name":"event scenarios","score":0.8679999709129333},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"unsupervised learning","score":0.7590000033378601},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"latent Dirichlet allocation","score":0.9599999785423279},{"id":"https://openalex.org/keywords/event-annotation","display_name":"event annotation","score":0.4790000021457672},{"id":"https://openalex.org/keywords/framenet","display_name":"FrameNet","score":0.7900000214576721},{"id":"https://openalex.org/keywords/text-modeling","display_name":"text modeling","score":0.4129999876022339},{"id":"https://openalex.org/keywords/perplexity-reduction","display_name":"perplexity reduction","score":0.796999990940094}],"concepts":[{"id":"https://openalex.org/C100279451","wikidata":"https://www.wikidata.org/wiki/Q372193","display_name":"Perplexity","level":3,"score":0.9085747599601746},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.845331072807312},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7860080003738403},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.7630034685134888},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.661657989025116},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6375939846038818},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5859456658363342},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.552675724029541},{"id":"https://openalex.org/C2778828372","wikidata":"https://www.wikidata.org/wiki/Q5283209","display_name":"Distributional semantics","level":3,"score":0.42816731333732605},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34437647461891174},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2560039162635803},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.0640018880367279},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.662.6348","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.662.6348","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.aaai.org/Papers/FLAIRS/2008/FLAIRS08-038.pdf","raw_type":"text"},{"id":"mag:2129272839","doi":null,"is_oa":false,"landing_page_url":"http://adi.bejan.ro/papers/2008_FLAIRS_Bejan_UnsupDiscoveryEventScenarios.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W30314283","https://openalex.org/W125892352","https://openalex.org/W176121905","https://openalex.org/W1605174196","https://openalex.org/W1880262756","https://openalex.org/W2001082470","https://openalex.org/W2025441317","https://openalex.org/W2045738181","https://openalex.org/W2094951132","https://openalex.org/W2104924585","https://openalex.org/W2107034620","https://openalex.org/W2115792525","https://openalex.org/W2157906684","https://openalex.org/W2171706135"],"related_works":["https://openalex.org/W2151295812","https://openalex.org/W2171674772","https://openalex.org/W2186727304","https://openalex.org/W2949345771","https://openalex.org/W7096252400","https://openalex.org/W2128364334","https://openalex.org/W7096215165","https://openalex.org/W7095766211","https://openalex.org/W7099426003","https://openalex.org/W1986824047"],"abstract_inverted_index":{"We":[0,13,58],"propose":[1],"a":[2,19,26,87,108,117],"new":[3],"unsupervised":[4],"learning":[5],"approach":[6,30],"for":[7,90],"discovering":[8],"event":[9,16,56,63,71,92,102,113],"scenarios":[10,72,75,93],"from":[11],"texts.":[12],"interpret":[14],"an":[15,62],"scenario":[17,114],"as":[18],"collection":[20],"of":[21,52,120],"related":[22],"events":[23,53],"that":[24,94],"characterize":[25],"specific":[27],"situation.":[28],"The":[29,84],"uses":[31],"the":[32,49,68,101,112],"Latent":[33],"Dirichlet":[34],"Allocation":[35],"(LDA)":[36],"probabilistic":[37],"model":[38,115],"described":[39],"in":[40,77,97,100],"(Blei,":[41],"Ng,":[42],"&":[43,81],"Jordan":[44],"2003)":[45],"to":[46,55],"automatically":[47,69],"learn":[48],"probability":[50],"distribution":[51],"correspond-ing":[54],"scenarios.":[57],"performed":[59],"experiments":[60],"on":[61],"annotated":[64,103],"cor-pus":[65],"and":[66],"compared":[67,106],"extracted":[70],"with":[73,107],"frame":[74],"defined":[76],"FrameNet":[78],"(Baker,":[79],"Fillmore,":[80],"Lowe":[82],"1998).":[83],"results":[85],"show":[86],"better":[88],"coverage":[89],"those":[91],"are":[95],"de-scribed":[96],"more":[98],"detail":[99],"corpus.":[104],"When":[105],"smoothed":[109],"unigram":[110],"model,":[111],"achieves":[116],"perplexity":[118],"reduction":[119],"93.46%.":[121]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":4}],"updated_date":"2026-10-12T09:40:04.860316","created_date":"2016-06-24T00:00:00"}