{"id":"https://openalex.org/W3091418863","doi":"https://doi.org/10.1145/3408313","title":"Time-Warped Sparse Non-negative Factorization for Functional Data Analysis","display_name":"Time-Warped Sparse Non-negative Factorization for Functional Data Analysis","publication_year":2020,"publication_date":"2020-09-28","ids":{"openalex":"https://openalex.org/W3091418863","doi":"https://doi.org/10.1145/3408313","mag":"3091418863"},"language":"en","primary_location":{"id":"doi:10.1145/3408313","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3408313","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-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/A5100374052","display_name":"Chen Zhang","orcid":"https://orcid.org/0000-0001-5773-9090"},"institutions":[{"id":"https://openalex.org/I79891267","display_name":"Singapore Management University","ror":"https://ror.org/050qmg959","country_code":"SG","type":"education","lineage":["https://openalex.org/I79891267"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Chen Zhang","raw_affiliation_strings":["Singapore Management University"],"affiliations":[{"raw_affiliation_string":"Singapore Management University","institution_ids":["https://openalex.org/I79891267"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074834854","display_name":"Steven C. H. Hoi","orcid":"https://orcid.org/0000-0002-4584-3453"},"institutions":[{"id":"https://openalex.org/I79891267","display_name":"Singapore Management University","ror":"https://ror.org/050qmg959","country_code":"SG","type":"education","lineage":["https://openalex.org/I79891267"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Steven C. H. Hoi","raw_affiliation_strings":["Singapore Management University"],"affiliations":[{"raw_affiliation_string":"Singapore Management University","institution_ids":["https://openalex.org/I79891267"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048627515","display_name":"Fugee Tsung","orcid":"https://orcid.org/0000-0002-0575-8254"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Fugee Tsung","raw_affiliation_strings":["Hong Kong University of Science and Technology"],"affiliations":[{"raw_affiliation_string":"Hong Kong University of Science and Technology","institution_ids":["https://openalex.org/I200769079"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100374052"],"corresponding_institution_ids":["https://openalex.org/I79891267"],"apc_list":null,"apc_paid":null,"fwci":0.4565,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.62136808,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":"14","issue":"6","first_page":"1","last_page":"23"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.991100013256073,"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"}},"topics":[{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.991100013256073,"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"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9878000020980835,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9718999862670898,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/factorization","display_name":"Factorization","score":0.7115636467933655},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.5961119532585144},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5714601874351501},{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"Dynamic time warping","score":0.5326749086380005},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.49508872628211975},{"id":"https://openalex.org/keywords/basis-function","display_name":"Basis function","score":0.4789636433124542},{"id":"https://openalex.org/keywords/matrix-decomposition","display_name":"Matrix decomposition","score":0.4603872299194336},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.45129722356796265},{"id":"https://openalex.org/keywords/variable","display_name":"Variable (mathematics)","score":0.4475215971469879},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.42404091358184814},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3979834318161011},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3927536606788635},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3439457416534424},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33420056104660034}],"concepts":[{"id":"https://openalex.org/C187834632","wikidata":"https://www.wikidata.org/wiki/Q188804","display_name":"Factorization","level":2,"score":0.7115636467933655},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.5961119532585144},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5714601874351501},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.5326749086380005},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.49508872628211975},{"id":"https://openalex.org/C5917680","wikidata":"https://www.wikidata.org/wiki/Q2621825","display_name":"Basis function","level":2,"score":0.4789636433124542},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.4603872299194336},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.45129722356796265},{"id":"https://openalex.org/C182365436","wikidata":"https://www.wikidata.org/wiki/Q50701","display_name":"Variable (mathematics)","level":2,"score":0.4475215971469879},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.42404091358184814},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3979834318161011},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3927536606788635},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3439457416534424},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33420056104660034},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3408313","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3408313","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7270416294","display_name":null,"funder_award_id":"71901131, 71932006, 71931006","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W905619","https://openalex.org/W16794263","https://openalex.org/W72893484","https://openalex.org/W146815106","https://openalex.org/W1540764732","https://openalex.org/W1583837637","https://openalex.org/W1847142364","https://openalex.org/W1878611151","https://openalex.org/W1902027874","https://openalex.org/W1986788466","https://openalex.org/W1987924891","https://openalex.org/W1994326236","https://openalex.org/W2038395331","https://openalex.org/W2058564856","https://openalex.org/W2064076655","https://openalex.org/W2071216735","https://openalex.org/W2071334094","https://openalex.org/W2078993594","https://openalex.org/W2080501585","https://openalex.org/W2091638851","https://openalex.org/W2091893102","https://openalex.org/W2093285006","https://openalex.org/W2102284541","https://openalex.org/W2110096996","https://openalex.org/W2118718620","https://openalex.org/W2121281940","https://openalex.org/W2128160875","https://openalex.org/W2129160848","https://openalex.org/W2130187411","https://openalex.org/W2130789253","https://openalex.org/W2132347401","https://openalex.org/W2137089646","https://openalex.org/W2140401203","https://openalex.org/W2140856955","https://openalex.org/W2155357014","https://openalex.org/W2156568029","https://openalex.org/W2162514423","https://openalex.org/W2168957377","https://openalex.org/W2169326025","https://openalex.org/W2170293972","https://openalex.org/W2294255557","https://openalex.org/W2341990530","https://openalex.org/W2406547137","https://openalex.org/W2562189683","https://openalex.org/W2594857575","https://openalex.org/W2740917292","https://openalex.org/W2776766374","https://openalex.org/W2790665460","https://openalex.org/W2793733641","https://openalex.org/W2931182523","https://openalex.org/W2949537047","https://openalex.org/W2963405869","https://openalex.org/W2963479420","https://openalex.org/W2964106494","https://openalex.org/W2978831816","https://openalex.org/W3014049250","https://openalex.org/W3082602295","https://openalex.org/W3143596294","https://openalex.org/W3144480685","https://openalex.org/W4292156489","https://openalex.org/W4408083158","https://openalex.org/W6675630042"],"related_works":["https://openalex.org/W4387497383","https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W2948807893","https://openalex.org/W2778153218","https://openalex.org/W2758277628","https://openalex.org/W1531601525","https://openalex.org/W1973739845","https://openalex.org/W119752240"],"abstract_inverted_index":{"This":[0],"article":[1],"proposes":[2],"a":[3,81],"novel":[4],"time-warped":[5],"sparse":[6],"non-negative":[7],"factorization":[8,56],"method":[9,16,51],"for":[10],"functional":[11],"data":[12,94],"analysis.":[13],"The":[14],"proposed":[15,78,102],"on":[17,35,80,92],"the":[18,22,36,50,60,96,101],"one":[19],"hand":[20,38],"guarantees":[21],"extracted":[23,61],"basis":[24,62],"functions":[25,45,63],"and":[26,32,34,57,98],"their":[27],"coefficients":[28],"to":[29,41,67],"be":[30],"positive":[31],"interpretable,":[33],"other":[37],"is":[39,77],"able":[40],"handle":[42],"weakly":[43],"correlated":[44],"with":[46,89],"different":[47,65],"features.":[48],"Furthermore,":[49],"incorporates":[52],"time":[53],"warping":[54],"into":[55],"hence":[58],"allows":[59],"of":[64,74,100],"samples":[66],"have":[68],"temporal":[69],"deformations.":[70],"An":[71],"efficient":[72],"framework":[73],"estimation":[75],"algorithms":[76],"based":[79],"greedy":[82],"variable":[83],"selection":[84],"approach.":[85],"Numerical":[86],"studies":[87,91],"together":[88],"case":[90],"real-world":[93],"demonstrate":[95],"efficacy":[97],"applicability":[99],"methodology.":[103]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2025-10-10T00:00:00"}