{"id":"https://openalex.org/W2057587538","doi":"https://doi.org/10.1145/2487575.2487682","title":"One theme in all views","display_name":"One theme in all views","publication_year":2013,"publication_date":"2013-08-11","ids":{"openalex":"https://openalex.org/W2057587538","doi":"https://doi.org/10.1145/2487575.2487682","mag":"2057587538"},"language":"en","primary_location":{"id":"doi:10.1145/2487575.2487682","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2487575.2487682","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5077231313","display_name":"Jian Tang","orcid":"https://orcid.org/0000-0002-6819-4185"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jian Tang","raw_affiliation_strings":["Peking University, Beijing, China","Peking University, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Peking University, Beijing, China#TAB#","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100642537","display_name":"Ming Zhang","orcid":"https://orcid.org/0000-0002-9809-3430"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Zhang","raw_affiliation_strings":["Peking University, Beijing, China","Peking University, Beijing, China#TAB#"],"affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Peking University, Beijing, China#TAB#","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048955398","display_name":"Qiaozhu Mei","orcid":"https://orcid.org/0000-0002-8640-1942"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qiaozhu Mei","raw_affiliation_strings":["University of Michigan, Ann Arbor, USA","University of Michigan , Ann Arbor , USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, USA","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"University of Michigan , Ann Arbor , USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5077231313"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":10.8450422,"has_fulltext":false,"cited_by_count":54,"citation_normalized_percentile":{"value":0.98430058,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"5","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9879999756813049,"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":0.9872999787330627,"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/computer-science","display_name":"Computer science","score":0.8148435950279236},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6108919382095337},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5916972160339355},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.5277693271636963},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.5172484517097473},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5111225247383118},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.4922162592411041},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4799659252166748},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.4686681032180786},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45697081089019775},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.44770506024360657},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43775075674057007},{"id":"https://openalex.org/keywords/data-type","display_name":"Data type","score":0.41715437173843384},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.37094035744667053},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10254737734794617}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8148435950279236},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6108919382095337},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5916972160339355},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.5277693271636963},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5172484517097473},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5111225247383118},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.4922162592411041},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4799659252166748},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.4686681032180786},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45697081089019775},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.44770506024360657},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43775075674057007},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.41715437173843384},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37094035744667053},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10254737734794617},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2487575.2487682","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2487575.2487682","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6200000047683716,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W105935508","https://openalex.org/W1536494821","https://openalex.org/W1880262756","https://openalex.org/W1965555277","https://openalex.org/W2001082470","https://openalex.org/W2042980227","https://openalex.org/W2044429219","https://openalex.org/W2063904635","https://openalex.org/W2076219102","https://openalex.org/W2092416660","https://openalex.org/W2096110600","https://openalex.org/W2101324110","https://openalex.org/W2102498033","https://openalex.org/W2107743791","https://openalex.org/W2108420397","https://openalex.org/W2108502868","https://openalex.org/W2127860643","https://openalex.org/W2130339025","https://openalex.org/W2137958601","https://openalex.org/W2140124448","https://openalex.org/W2147946282","https://openalex.org/W2149510050","https://openalex.org/W2150461699","https://openalex.org/W2151936673","https://openalex.org/W2154415691","https://openalex.org/W2157589241","https://openalex.org/W2159426623","https://openalex.org/W2168332560","https://openalex.org/W2171343266","https://openalex.org/W2979401726","https://openalex.org/W4233135949","https://openalex.org/W6680343917","https://openalex.org/W6680441624","https://openalex.org/W6682044806","https://openalex.org/W6682991666","https://openalex.org/W6769430610"],"related_works":["https://openalex.org/W2118717649","https://openalex.org/W2413243053","https://openalex.org/W410723623","https://openalex.org/W2015341305","https://openalex.org/W2035068594","https://openalex.org/W4225593417","https://openalex.org/W2573498121","https://openalex.org/W3022298670","https://openalex.org/W3160494304","https://openalex.org/W3006162251"],"abstract_inverted_index":{"New":[0],"challenges":[1],"have":[2,32],"been":[3,33],"presented":[4],"to":[5,11,29,46,99,123,159,192],"classical":[6,75,136],"topic":[7,51,55,76,137],"models":[8,31,56,77],"when":[9],"applied":[10],"social":[12],"media,":[13],"as":[14,145],"user-generated":[15],"content":[16],"suffers":[17],"from":[18,175],"significant":[19],"problems":[20],"of":[21,26,36,43,50,61,74,105,127,132,135,143,148,151,196],"data":[22],"sparseness.":[23],"A":[24,154],"variety":[25],"heuristic":[27],"adjustments":[28],"these":[30,161],"proposed,":[34],"many":[35],"which":[37],"are":[38],"based":[39],"on":[40,58],"the":[41,48,62,71,133,149,152,169,184],"use":[42],"context":[44,68],"information":[45],"improve":[47],"performance":[49],"modeling.":[52],"Existing":[53],"contextualized":[54],"rely":[57],"arbitrary":[59,101,130,194],"manipulation":[60,131],"model":[63,91],"structure,":[64],"by":[65],"incorporating":[66],"various":[67],"variables":[69],"into":[70],"generative":[72],"process":[73],"in":[78,87],"an":[79],"ad":[80],"hoc":[81],"manner.":[82],"Such":[83],"manipulations":[84],"usually":[85],"result":[86],"much":[88],"more":[89],"complicated":[90],"structures,":[92],"sophisticated":[93],"inference":[94],"procedures,":[95],"and":[96,172,190],"low":[97],"generalizability":[98],"accommodate":[100],"types":[102,126,142,195],"or":[103],"combinations":[104],"contexts.":[106,197],"In":[107],"this":[108],"paper":[109],"we":[110],"explore":[111],"a":[112,117],"different":[113,141],"direction.":[114],"We":[115,139],"propose":[116],"general":[118],"solution":[119],"that":[120,183],"is":[121,157,187],"able":[122],"exploit":[124],"multiple":[125,146],"contexts":[128,144],"without":[129],"structure":[134],"models.":[138],"formulate":[140],"views":[147,162],"partition":[150],"corpus.":[153],"co-regularization":[155],"framework":[156],"proposed":[158,185],"let":[160],"collaborate":[163],"with":[164,179],"each":[165],"other,":[166],"vote":[167],"for":[168],"consensus":[170],"topics,":[171],"distinguish":[173],"them":[174],"view-specific":[176],"topics.":[177],"Experiments":[178],"real-world":[180],"datasets":[181],"prove":[182],"method":[186],"both":[188],"effective":[189],"flexible":[191],"handle":[193]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":9},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}