{"id":"https://openalex.org/W2066727938","doi":"https://doi.org/10.1145/1076034.1076055","title":"A probabilistic model for retrospective news event detection","display_name":"A probabilistic model for retrospective news event detection","publication_year":2005,"publication_date":"2005-08-15","ids":{"openalex":"https://openalex.org/W2066727938","doi":"https://doi.org/10.1145/1076034.1076055","mag":"2066727938"},"language":"en","primary_location":{"id":"doi:10.1145/1076034.1076055","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1076034.1076055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5100618669","display_name":"Zhiwei Li","orcid":"https://orcid.org/0000-0002-3378-3457"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiwei Li","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China","Microsoft research Asia, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"Microsoft research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108156794","display_name":"Bin Wang","orcid":"https://orcid.org/0000-0002-3790-2708"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Wang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China",", University of Science and Technology of China, Hefei, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]},{"raw_affiliation_string":", University of Science and Technology of China, Hefei, China#TAB#","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061131131","display_name":"Mingjing Li","orcid":"https://orcid.org/0000-0002-5290-8104"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingjing Li","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China","Microsoft research Asia, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"Microsoft research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103733614","display_name":"Wei\u2010Ying Ma","orcid":"https://orcid.org/0000-0002-7384-0735"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei-Ying Ma","raw_affiliation_strings":["Microsoft Research Asia, Beijing, China","Microsoft research Asia, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"Microsoft research Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":25.4402,"has_fulltext":false,"cited_by_count":184,"citation_normalized_percentile":{"value":0.99342658,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"106","last_page":"113"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11439","display_name":"Video Analysis and Summarization","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9951000213623047,"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":0.7345561385154724},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.722531795501709},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.7217631340026855},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6864562630653381},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5526993274688721},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.5238573551177979},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5102121829986572},{"id":"https://openalex.org/keywords/fake-news","display_name":"Fake news","score":0.4374573528766632},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4257390797138214},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2312471568584442},{"id":"https://openalex.org/keywords/internet-privacy","display_name":"Internet privacy","score":0.133864164352417}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7345561385154724},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.722531795501709},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.7217631340026855},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6864562630653381},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5526993274688721},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.5238573551177979},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5102121829986572},{"id":"https://openalex.org/C2779756789","wikidata":"https://www.wikidata.org/wiki/Q28549308","display_name":"Fake news","level":2,"score":0.4374573528766632},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4257390797138214},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2312471568584442},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.133864164352417},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1076034.1076055","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1076034.1076055","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.90.9651","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.90.9651","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://research.microsoft.com/asia/dload_files/group/wsm/SigIR2005/A Probabilistic Model for Retrospective News Event Detection.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1520377376","https://openalex.org/W1522930108","https://openalex.org/W1554944419","https://openalex.org/W1981825277","https://openalex.org/W1998224037","https://openalex.org/W2007760849","https://openalex.org/W2055294489","https://openalex.org/W2064988570","https://openalex.org/W2097005391","https://openalex.org/W2097089247","https://openalex.org/W2169279737","https://openalex.org/W4234917632"],"related_works":["https://openalex.org/W2380075625","https://openalex.org/W2890339288","https://openalex.org/W2966672946","https://openalex.org/W3205414356","https://openalex.org/W3137554057","https://openalex.org/W3015693164","https://openalex.org/W2942388309","https://openalex.org/W2996237090","https://openalex.org/W3137972732","https://openalex.org/W4385572368"],"abstract_inverted_index":{"Retrospective":[0],"news":[1,16,26,42,75,81,103,112,152,155],"event":[2,97],"detection":[3],"(RED)":[4],"is":[5],"defined":[6],"as":[7],"the":[8,20,36,39,70,78,89,95,115],"discovery":[9],"of":[10,25,38,41,55,74,111,126,150],"previously":[11],"unidentified":[12],"events":[13],"in":[14,141],"historical":[15],"corpus.":[17],"Although":[18],"both":[19,66,136,151],"contents":[21,40],"and":[22,114,138,154,178],"time":[23,56,139],"information":[24,140],"articles":[27,82,93,153],"are":[28,83],"helpful":[29],"to":[30,121,134,173],"RED,":[31],"most":[32],"researches":[33],"focus":[34],"on":[35,51,65,69,88,101,159],"utilization":[37],"articles.":[43,76],"Few":[44],"research":[45],"works":[46],"have":[47],"been":[48],"carried":[49],"out":[50],"finding":[52],"better":[53],"usages":[54],"information.":[57],"In":[58],"this":[59,160],"paper,":[60],"we":[61,129,162],"do":[62],"some":[63],"explorations":[64],"directions":[67],"based":[68,158],"following":[71],"two":[72],"characteristics":[73],"On":[77],"one":[79],"hand,":[80,91],"always":[84],"aroused":[85],"by":[86],"events;":[87],"other":[90],"similar":[92],"reporting":[94],"same":[96],"often":[98],"redundantly":[99],"appear":[100],"many":[102],"sources.":[104],"The":[105],"former":[106],"hints":[107],"a":[108,131,142],"generative":[109],"model":[110,133,146],"articles,":[113],"latter":[116],"provides":[117,170],"data":[118],"enriched":[119],"environments":[120],"perform":[122],"RED.":[123],"With":[124],"consideration":[125],"these":[127],"characteristics,":[128],"propose":[130],"probabilistic":[132],"incorporate":[135],"content":[137],"unified":[143],"framework.":[144],"This":[145],"gives":[147],"new":[148],"representations":[149],"events.":[156],"Furthermore,":[157],"approach,":[161],"build":[163],"an":[164],"interactive":[165],"RED":[166],"system,":[167],"HISCOVERY,":[168],"which":[169],"additional":[171],"functions":[172],"present":[174],"events,":[175],"Photo":[176],"Story":[177],"Chronicle.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":7},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":12},{"year":2015,"cited_by_count":16},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":17},{"year":2012,"cited_by_count":10}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}