{"id":"https://openalex.org/W2114864409","doi":"https://doi.org/10.18653/v1/d13-1002","title":"Exploiting Discourse Analysis for Article-Wide Temporal Classification","display_name":"Exploiting Discourse Analysis for Article-Wide Temporal Classification","publication_year":2013,"publication_date":"2013-01-01","ids":{"openalex":"https://openalex.org/W2114864409","doi":"https://doi.org/10.18653/v1/d13-1002","mag":"2114864409"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d13-1002","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d13-1002","pdf_url":"https://aclanthology.org/D13-1002.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 2013 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://aclanthology.org/D13-1002.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056813874","display_name":"Jun-Ping Ng","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Jun-Ping Ng","raw_affiliation_strings":["National University of Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066305082","display_name":"Min\u2010Yen Kan","orcid":"https://orcid.org/0000-0001-8507-3716"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Min-Yen Kan","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000590701","display_name":"Ziheng Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Ziheng Lin","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081703144","display_name":"Wei Feng","orcid":"https://orcid.org/0000-0002-9993-8722"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Feng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100427454","display_name":"Bin Chen","orcid":"https://orcid.org/0009-0002-1411-7915"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bin Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101860993","display_name":"Jian Su","orcid":"https://orcid.org/0009-0001-9484-5885"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jian Su","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5111664929","display_name":"Chew Lim Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chew-Lim Tan","raw_affiliation_strings":["National University of Singapore, Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Singapore, Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.9648,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.91925489,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"12","last_page":"23"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9983999729156494,"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":0.8292027711868286},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7577091455459595},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.7270922064781189},{"id":"https://openalex.org/keywords/rhetorical-question","display_name":"Rhetorical question","score":0.6260044574737549},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6127086877822876},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.576992392539978},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5407926440238953},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4561857283115387},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4349592924118042},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.4280681014060974},{"id":"https://openalex.org/keywords/discourse-analysis","display_name":"Discourse analysis","score":0.4210663437843323},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.2549940347671509}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8292027711868286},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7577091455459595},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.7270922064781189},{"id":"https://openalex.org/C192562157","wikidata":"https://www.wikidata.org/wiki/Q316694","display_name":"Rhetorical question","level":2,"score":0.6260044574737549},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6127086877822876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.576992392539978},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5407926440238953},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4561857283115387},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4349592924118042},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.4280681014060974},{"id":"https://openalex.org/C84389358","wikidata":"https://www.wikidata.org/wiki/Q1129466","display_name":"Discourse analysis","level":2,"score":0.4210663437843323},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.2549940347671509},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.18653/v1/d13-1002","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d13-1002","pdf_url":"https://aclanthology.org/D13-1002.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 2013 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.377.1","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.377.1","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.comp.nus.edu.sg/~kanmy/papers/emnlp2013.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.593.5450","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.593.5450","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/D13/D13-1002.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.18653/v1/d13-1002","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d13-1002","pdf_url":"https://aclanthology.org/D13-1002.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 2013 Conference on Empirical Methods in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","score":0.6100000143051147,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320320709","display_name":"National Research Foundation Singapore","ror":"https://ror.org/03cpyc314"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2114864409.pdf","grobid_xml":"https://content.openalex.org/works/W2114864409.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W40273907","https://openalex.org/W77146693","https://openalex.org/W173536012","https://openalex.org/W1496244604","https://openalex.org/W1505640402","https://openalex.org/W1563792215","https://openalex.org/W1571872475","https://openalex.org/W1587871245","https://openalex.org/W1690833673","https://openalex.org/W1964135532","https://openalex.org/W1991169218","https://openalex.org/W2045738181","https://openalex.org/W2057905685","https://openalex.org/W2060381885","https://openalex.org/W2098844768","https://openalex.org/W2100873065","https://openalex.org/W2104950474","https://openalex.org/W2110568314","https://openalex.org/W2127194753","https://openalex.org/W2127713198","https://openalex.org/W2135586429","https://openalex.org/W2137320444","https://openalex.org/W2140244223","https://openalex.org/W2145164276","https://openalex.org/W2150741878","https://openalex.org/W2156909104","https://openalex.org/W2166957049","https://openalex.org/W2251650185","https://openalex.org/W2949496004","https://openalex.org/W3029289454","https://openalex.org/W3088311774","https://openalex.org/W3146981046"],"related_works":["https://openalex.org/W2594084610","https://openalex.org/W2779608055","https://openalex.org/W1975975036","https://openalex.org/W600290691","https://openalex.org/W1990962480","https://openalex.org/W4386073139","https://openalex.org/W123503334","https://openalex.org/W4400470172","https://openalex.org/W4308202662","https://openalex.org/W2259409290"],"abstract_inverted_index":{"In":[0],"this":[1],"paper":[2],"we":[3,42,48,129],"classify":[4],"the":[5,22,35,62,113],"temporal":[6],"relations":[7],"between":[8],"pairs":[9,30],"of":[10,21,64,123,139],"events":[11],"on":[12,27,44,112],"an":[13],"article-wide":[14],"basis.This":[15],"is":[16,108],"in":[17,110,121],"contrast":[18],"to":[19,148],"much":[20,118],"existing":[23],"literature":[24],"which":[25,31],"focuses":[26],"just":[28],"event":[29],"are":[32],"found":[33],"within":[34],"same":[36],"or":[37],"adjacent":[38],"sentences.To":[39],"achieve":[40],"this,":[41],"leverage":[43],"discourse":[45,66,77,134,142],"analysis":[46,67,143],"as":[47,117,119],"believe":[49],"that":[50,105],"it":[51],"provides":[52],"more":[53,140],"useful":[54],"semantic":[55],"information":[56],"than":[57],"typical":[58],"lexico-syntactic":[59],"features.We":[60],"propose":[61],"use":[63,138],"several":[65],"frameworks,":[68],"including":[69],"1)":[70],"Rhetorical":[71],"Structure":[72],"Theory":[73],"(RST),":[74],"2)":[75],"PDTB-styled":[76],"relations,":[78],"and":[79,136],"3)":[80],"topical":[81],"text":[82],"segmentation.We":[83],"explain":[84],"how":[85],"features":[86],"derived":[87],"from":[88],"these":[89],"frameworks":[90],"can":[91,144],"be":[92],"effectively":[93],"used":[94],"with":[95,101],"support":[96],"vector":[97],"machines":[98],"(SVM)":[99],"paired":[100],"convolution":[102],"kernels.Experiments":[103],"show":[104],"our":[106],"proposal":[107],"effective":[109],"improving":[111],"state-of-the-art":[114],"significantly":[115],"by":[116],"16%":[120],"terms":[122],"F":[124],"1":[125],",":[126],"even":[127],"if":[128],"only":[130],"adopt":[131],"less-than-perfect":[132],"automatic":[133],"analyzers":[135],"parsers.Making":[137],"accurate":[141],"further":[145],"boost":[146],"gains":[147],"35%.":[149]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}