{"id":"https://openalex.org/W2161152810","doi":"https://doi.org/10.1145/1281192.1281249","title":"Multiscale topic tomography","display_name":"Multiscale topic tomography","publication_year":2007,"publication_date":"2007-08-12","ids":{"openalex":"https://openalex.org/W2161152810","doi":"https://doi.org/10.1145/1281192.1281249","mag":"2161152810"},"language":"en","primary_location":{"id":"doi:10.1145/1281192.1281249","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1281192.1281249","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th 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/A5109250040","display_name":"Ramesh Nallapati","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ramesh M. Nallapati","raw_affiliation_strings":["Carnegie Mellon University"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045904161","display_name":"Susan Ditmore","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Susan Ditmore","raw_affiliation_strings":["Carnegie Mellon University"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060219657","display_name":"John Lafferty","orcid":"https://orcid.org/0000-0002-5929-220X"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John D. Lafferty","raw_affiliation_strings":["Carnegie Mellon University"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012064766","display_name":"Kin Ung","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135437","display_name":"Johnson & Johnson (Israel)","ror":"https://ror.org/03kzp5v39","country_code":"IL","type":"company","lineage":["https://openalex.org/I1330063522","https://openalex.org/I4210135437"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Kin Ung","raw_affiliation_strings":["Johnson and Johnson group"],"affiliations":[{"raw_affiliation_string":"Johnson and Johnson group","institution_ids":["https://openalex.org/I4210135437"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5109250040"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":7.7274,"has_fulltext":false,"cited_by_count":60,"citation_normalized_percentile":{"value":0.97188558,"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":"520","last_page":"529"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9902999997138977,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9902999997138977,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9876000285148621,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9819999933242798,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/perplexity","display_name":"Perplexity","score":0.8771377205848694},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7741261720657349},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.7624984979629517},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.6385180950164795},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48802104592323303},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.43959206342697144},{"id":"https://openalex.org/keywords/zoom","display_name":"Zoom","score":0.4360572397708893},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4189629554748535},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3917072117328644},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33749884366989136},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.32550737261772156},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.2588346600532532}],"concepts":[{"id":"https://openalex.org/C100279451","wikidata":"https://www.wikidata.org/wiki/Q372193","display_name":"Perplexity","level":3,"score":0.8771377205848694},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7741261720657349},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.7624984979629517},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.6385180950164795},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48802104592323303},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.43959206342697144},{"id":"https://openalex.org/C124913957","wikidata":"https://www.wikidata.org/wiki/Q1232548","display_name":"Zoom","level":3,"score":0.4360572397708893},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4189629554748535},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3917072117328644},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33749884366989136},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32550737261772156},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.2588346600532532},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C78762247","wikidata":"https://www.wikidata.org/wiki/Q1273174","display_name":"Petroleum engineering","level":1,"score":0.0},{"id":"https://openalex.org/C15336307","wikidata":"https://www.wikidata.org/wiki/Q1766051","display_name":"Lens (geology)","level":2,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/1281192.1281249","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1281192.1281249","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.127.5633","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.127.5633","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.cmu.edu/~nmramesh/tt.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.72.9012","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.72.9012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www-2.cs.cmu.edu/~wcohen/postscript/topic-tomography-submitted.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1499624045","https://openalex.org/W1516111018","https://openalex.org/W1742810160","https://openalex.org/W1880262756","https://openalex.org/W1986966428","https://openalex.org/W2014415866","https://openalex.org/W2060637162","https://openalex.org/W2072644219","https://openalex.org/W2112050062","https://openalex.org/W2112971401","https://openalex.org/W2135236030","https://openalex.org/W2158266063","https://openalex.org/W2171343266","https://openalex.org/W2595697910","https://openalex.org/W2990138404","https://openalex.org/W4231510805","https://openalex.org/W6639619044","https://openalex.org/W6676893574"],"related_works":["https://openalex.org/W2376415519","https://openalex.org/W1601381279","https://openalex.org/W4294769427","https://openalex.org/W4293734197","https://openalex.org/W2169401934","https://openalex.org/W4206967254","https://openalex.org/W2131689821","https://openalex.org/W3117044075","https://openalex.org/W2278712165","https://openalex.org/W2168471263"],"abstract_inverted_index":{"Modeling":[0],"the":[1,40,70,74,79,89,97,105],"evolution":[2,56,80],"of":[3,8,16,53,57,69,73,81,86,96],"topics":[4,58,82],"with":[5],"time":[6],"is":[7,59,76,117],"great":[9],"value":[10],"in":[11,93,112,122],"automatic":[12],"summarization":[13],"and":[14,94],"analysis":[15,64],"large":[17],"document":[18],"collections.":[19],"In":[20],"this":[21,32],"work,":[22],"we":[23,38],"propose":[24],"a":[25,62],"new":[26,35,71,106,115],"probabilistic":[27],"graphical":[28],"model":[29,51,75,107,116],"to":[30,50,91,120],"address":[31],"issue.":[33],"The":[34,55,114],"model,":[36],"which":[37],"call":[39],"Multiscale":[41],"Topic":[42],"Tomography":[43],"Model":[44],"(MTTM),":[45],"employs":[46],"non-homogeneous":[47],"Poisson":[48],"processes":[49],"generation":[52],"word-counts.":[54],"modeled":[60],"through":[61],"multi-scale":[63],"using":[65,104],"Haar":[66],"wavelets.":[67],"One":[68],"features":[72],"its":[77],"modeling":[78],"at":[83],"various":[84],"time-scales":[85],"resolution,":[87],"allowing":[88],"user":[90],"zoom":[92],"out":[95],"time-scales.":[98],"Our":[99],"experiments":[100],"on":[101],"Science":[102],"data":[103,125],"uncovers":[108],"some":[109],"interesting":[110],"patterns":[111],"topics.":[113],"also":[118],"comparable":[119],"LDA":[121],"predicting":[123],"unseen":[124],"as":[126],"demonstrated":[127],"by":[128],"our":[129],"perplexity":[130],"experiments.":[131]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":4}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
