{"id":"https://openalex.org/W2898346288","doi":"https://doi.org/10.1109/asonam.2018.8508739","title":"Constrained Coupled Matrix-Tensor Factorization and its Application in Pattern and Topic Detection","display_name":"Constrained Coupled Matrix-Tensor Factorization and its Application in Pattern and Topic Detection","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2898346288","doi":"https://doi.org/10.1109/asonam.2018.8508739","mag":"2898346288"},"language":"en","primary_location":{"id":"doi:10.1109/asonam.2018.8508739","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam.2018.8508739","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","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/A5074547230","display_name":"Sanaz Bahargam","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Sanaz Bahargam","raw_affiliation_strings":["Boston University"],"affiliations":[{"raw_affiliation_string":"Boston University","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054849323","display_name":"Evangelos E. Papalexakis","orcid":"https://orcid.org/0000-0002-3411-8483"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Evangelos E. Papalexakis","raw_affiliation_strings":["University of California, Riverside"],"affiliations":[{"raw_affiliation_string":"University of California, Riverside","institution_ids":["https://openalex.org/I103635307"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5074547230"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.4725,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.78041958,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"91","last_page":"94"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9966999888420105,"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":0.9671000242233276,"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":0.7439101338386536},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.626624345779419},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.6106749773025513},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.586531400680542},{"id":"https://openalex.org/keywords/non-negative-matrix-factorization","display_name":"Non-negative matrix factorization","score":0.5425347685813904},{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.5375487804412842},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.45283859968185425},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4489639103412628},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4051634669303894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3606652021408081},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3535461127758026},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3217623233795166},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.16729530692100525},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14108127355575562}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7439101338386536},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.626624345779419},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.6106749773025513},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.586531400680542},{"id":"https://openalex.org/C152671427","wikidata":"https://www.wikidata.org/wiki/Q10843505","display_name":"Non-negative matrix factorization","level":4,"score":0.5425347685813904},{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.5375487804412842},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.45283859968185425},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4489639103412628},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4051634669303894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3606652021408081},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3535461127758026},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3217623233795166},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.16729530692100525},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14108127355575562},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/asonam.2018.8508739","is_oa":false,"landing_page_url":"https://doi.org/10.1109/asonam.2018.8508739","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W111803032","https://openalex.org/W2047680880","https://openalex.org/W2561158044","https://openalex.org/W2810217019","https://openalex.org/W2963999633","https://openalex.org/W6604521660","https://openalex.org/W6637310804","https://openalex.org/W6730036397"],"related_works":["https://openalex.org/W4390394189","https://openalex.org/W2037504162","https://openalex.org/W2539013788","https://openalex.org/W2792706544","https://openalex.org/W1568451138","https://openalex.org/W2156699640","https://openalex.org/W2045265907","https://openalex.org/W2972997031","https://openalex.org/W2146544734","https://openalex.org/W2075222291"],"abstract_inverted_index":{"Traditionally,":[0],"time-evolving":[1,67],"topic":[2,13,57,68,86,141],"discovery":[3,69],"approaches":[4],"have":[5],"focused":[6],"on":[7,116],"the":[8,12,35,40,45,48,51,53,56,75,82,92,104],"temporal":[9],"evolution":[10,83],"of":[11,32,42,44,84,94,96,106,108,120],"itself.":[14],"However,":[15],"especially":[16],"in":[17,72],"settings":[18],"where":[19],"content":[20,46],"is":[21,34,78,101,114],"contributed":[22],"by":[23,103],"a":[24,27,65,117],"community":[25],"or":[26],"crowd,":[28],"an":[29],"orthogonal":[30],"notion":[31],"time":[33],"one":[36],"that":[37,85,97,128],"pertains":[38],"to":[39,74,80],"level":[41,93,105],"expertise":[43,107],"creator:":[47],"more":[49,54],"experienced":[50],"creator,":[52],"advanced":[55],"will":[58],"be.":[59],"In":[60],"this":[61],"paper,":[62],"we":[63,135],"propose":[64],"novel":[66,118],"method":[70,113],"which,":[71],"addition":[73],"extracted":[76],"topics,":[77],"able":[79],"identify":[81],"over":[87],"time,":[88],"as":[89,91,99,134],"well":[90,130],"difficulty":[95],"topic,":[98],"it":[100],"inferred":[102],"its":[109],"main":[110],"contributors.":[111],"Our":[112],"based":[115],"formulation":[119],"Constrained":[121],"Coupled":[122],"Matrix-Tensor":[123],"Factorization,":[124],"which":[125],"adopts":[126],"constraints":[127],"are":[129,137],"motivated":[131],"for,":[132],"and,":[133],"demonstrate,":[136],"necessary":[138],"for":[139],"high-quality":[140],"discovery.":[142]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}