{"id":"https://openalex.org/W2107628405","doi":"https://doi.org/10.1145/2063576.2063686","title":"Emerging topic detection using dictionary learning","display_name":"Emerging topic detection using dictionary learning","publication_year":2011,"publication_date":"2011-10-24","ids":{"openalex":"https://openalex.org/W2107628405","doi":"https://doi.org/10.1145/2063576.2063686","mag":"2107628405"},"language":"en","primary_location":{"id":"doi:10.1145/2063576.2063686","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2063576.2063686","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th ACM international conference on Information and knowledge management","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/A5036801391","display_name":"Shiva Prasad Kasiviswanathan","orcid":"https://orcid.org/0000-0002-1725-2621"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Shiva Prasad Kasiviswanathan","raw_affiliation_strings":["IBM TJ Watson Research, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM TJ Watson Research, Yorktown Heights, NY, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112555367","display_name":"Prem Melville","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Prem Melville","raw_affiliation_strings":["IBM TJ Watson Research, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM TJ Watson Research, Yorktown Heights, NY, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014459472","display_name":"Arindam Banerjee","orcid":"https://orcid.org/0000-0002-7856-5699"},"institutions":[{"id":"https://openalex.org/I4210101327","display_name":"Twin Cities Orthopedics","ror":"https://ror.org/01en4s460","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210101327"]},{"id":"https://openalex.org/I130238516","display_name":"University of Minnesota","ror":"https://ror.org/017zqws13","country_code":"US","type":"education","lineage":["https://openalex.org/I130238516"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Arindam Banerjee","raw_affiliation_strings":["University of Minnesota, Twin Cities, MN, USA"],"affiliations":[{"raw_affiliation_string":"University of Minnesota, Twin Cities, MN, USA","institution_ids":["https://openalex.org/I4210101327","https://openalex.org/I130238516"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058073838","display_name":"Vikas Sindhwani","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vikas Sindhwani","raw_affiliation_strings":["IBM TJ Watson Research, Yorktown Heights, NY, USA"],"affiliations":[{"raw_affiliation_string":"IBM TJ Watson Research, Yorktown Heights, NY, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5036801391"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.21,"has_fulltext":false,"cited_by_count":128,"citation_normalized_percentile":{"value":0.9904012,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"19","issue":null,"first_page":"745","last_page":"754"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9961000084877014,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9894000291824341,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8431879281997681},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.8038188815116882},{"id":"https://openalex.org/keywords/microblogging","display_name":"Microblogging","score":0.7452280521392822},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6347931623458862},{"id":"https://openalex.org/keywords/streaming-data","display_name":"Streaming data","score":0.5732704401016235},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5692882537841797},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5453585386276245},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.4998798370361328},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.4359709322452545},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.4297170341014862},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.390877902507782},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24257078766822815},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2146378755569458}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8431879281997681},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.8038188815116882},{"id":"https://openalex.org/C143275388","wikidata":"https://www.wikidata.org/wiki/Q92438","display_name":"Microblogging","level":3,"score":0.7452280521392822},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6347931623458862},{"id":"https://openalex.org/C2777611316","wikidata":"https://www.wikidata.org/wiki/Q39045282","display_name":"Streaming data","level":2,"score":0.5732704401016235},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5692882537841797},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5453585386276245},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.4998798370361328},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.4359709322452545},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.4297170341014862},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.390877902507782},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24257078766822815},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2146378755569458},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","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},{"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:10.1145/2063576.2063686","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2063576.2063686","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th ACM international conference on Information and knowledge management","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.372.7934","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.372.7934","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cse.psu.edu/~kasivisw/cikm.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7200000286102295}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W33214042","https://openalex.org/W1532325895","https://openalex.org/W1594112393","https://openalex.org/W1599867596","https://openalex.org/W1612003148","https://openalex.org/W1636387013","https://openalex.org/W1790954942","https://openalex.org/W1880262756","https://openalex.org/W1902027874","https://openalex.org/W1946620893","https://openalex.org/W1963548240","https://openalex.org/W1976709621","https://openalex.org/W1983008863","https://openalex.org/W1983012012","https://openalex.org/W1986931325","https://openalex.org/W2019585163","https://openalex.org/W2059503205","https://openalex.org/W2071940869","https://openalex.org/W2075779886","https://openalex.org/W2082855665","https://openalex.org/W2096586829","https://openalex.org/W2101117936","https://openalex.org/W2101868363","https://openalex.org/W2105464873","https://openalex.org/W2109921208","https://openalex.org/W2112447569","https://openalex.org/W2113606819","https://openalex.org/W2114147096","https://openalex.org/W2129812935","https://openalex.org/W2135046866","https://openalex.org/W2139043937","https://openalex.org/W2140427797","https://openalex.org/W2153636395","https://openalex.org/W2160547390","https://openalex.org/W2164278908","https://openalex.org/W2165916500","https://openalex.org/W2949483514","https://openalex.org/W2951443864","https://openalex.org/W3083798602","https://openalex.org/W4292363360","https://openalex.org/W4300613059","https://openalex.org/W6636440780","https://openalex.org/W7007911130","https://openalex.org/W7066004807"],"related_works":["https://openalex.org/W2275433313","https://openalex.org/W2053241453","https://openalex.org/W2017590198","https://openalex.org/W2978974359","https://openalex.org/W2036556872","https://openalex.org/W2728430307","https://openalex.org/W2153980712","https://openalex.org/W2107786128","https://openalex.org/W2087532526","https://openalex.org/W1805578373"],"abstract_inverted_index":{"Streaming":[0],"user-generated":[1,111],"content":[2],"in":[3,143,147],"the":[4,29,42,49,55,66,85,92,120,126,157],"form":[5],"of":[6,18,32,41,52,68,87,94,109],"blogs,":[7],"microblogs,":[8],"forums,":[9],"and":[10,24,107,151],"multimedia":[11],"sharing":[12],"sites,":[13],"provides":[14],"a":[15,72,99,115,166],"rich":[16],"source":[17],"data":[19,36,170],"from":[20,54,79,171],"which":[21,76],"invaluable":[22],"information":[23],"insights":[25],"maybe":[26],"gleaned.":[27],"Given":[28],"vast":[30],"volume":[31],"such":[33],"social":[34,161],"media":[35,162],"being":[37],"continually":[38],"generated,":[39],"one":[40],"challenges":[43],"is":[44,77,137],"to":[45,124,160],"automatically":[46],"tease":[47],"apart":[48],"emerging":[50,60,89,145],"topics":[51,61,90,146],"discussion":[53],"constant":[56],"background":[57],"chatter.":[58],"Such":[59],"can":[62],"be":[63],"identified":[64],"by":[65,118],"appearance":[67],"multiple":[69],"posts":[70],"on":[71,105,165,168],"unique":[73],"subject":[74],"matter,":[75],"distinct":[78],"previous":[80],"online":[81],"discourse.":[82],"We":[83,97,113,154],"address":[84],"problem":[86],"identifying":[88],"through":[91],"use":[93],"dictionary":[95],"learning.":[96],"propose":[98],"two":[100],"stage":[101],"approach":[102,117,136],"respectively":[103],"based":[104,164],"detection":[106],"clustering":[108],"novel":[110],"content.":[112],"derive":[114],"scalable":[116],"using":[119],"alternating":[121],"directions":[122],"method":[123],"solve":[125],"resulting":[127],"optimization":[128],"problems.":[129],"Empirical":[130],"results":[131],"show":[132],"that":[133],"our":[134],"proposed":[135],"more":[138],"effective":[139],"than":[140],"several":[141],"baselines":[142],"detecting":[144],"traditional":[148],"news":[149],"story":[150],"newsgroup":[152],"data.":[153],"also":[155],"demonstrate":[156],"practical":[158],"application":[159],"analysis,":[163],"study":[167],"streaming":[169],"Twitter.":[172]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":15},{"year":2016,"cited_by_count":14},{"year":2015,"cited_by_count":10},{"year":2014,"cited_by_count":16},{"year":2013,"cited_by_count":21},{"year":2012,"cited_by_count":14}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
