{"id":"https://openalex.org/W2126917700","doi":"https://doi.org/10.5555/2627435.2670314","title":"Sparse factor analysis for learning and content analytics","display_name":"Sparse factor analysis for learning and content analytics","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2126917700","doi":"https://doi.org/10.5555/2627435.2670314","mag":"2126917700"},"language":"en","primary_location":{"id":"pmh:oai:CiteSeerX.psu:10.1.1.715.4749","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.715.4749","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.csl.cornell.edu/%7Estuder/papers/14JMLR-sparfa.pdf","raw_type":"text"},"type":"article","indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1303.5685","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5063813962","display_name":"Andrew Lan","orcid":"https://orcid.org/0000-0002-8475-6600"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew Lan","raw_affiliation_strings":["Dept. Electrical and Computer Engineering, Rice University, Houston, TX#TAB#"],"raw_orcid":"https://orcid.org/0000-0002-8475-6600","affiliations":[{"raw_affiliation_string":"Dept. Electrical and Computer Engineering, Rice University, Houston, TX#TAB#","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061631706","display_name":"Andrew E. Waters","orcid":null},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andrew E. Waters","raw_affiliation_strings":["Dept. Electrical and Computer Engineering, Rice University, Houston, TX#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. Electrical and Computer Engineering, Rice University, Houston, TX#TAB#","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083617223","display_name":"Christoph Studer","orcid":"https://orcid.org/0000-0001-8950-6267"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christoph Studer","raw_affiliation_strings":["[School of Electrical and Computer Engineering, Cornell University, Ithaca, NY.]"],"raw_orcid":"https://orcid.org/0000-0001-8950-6267","affiliations":[{"raw_affiliation_string":"[School of Electrical and Computer Engineering, Cornell University, Ithaca, NY.]","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072713767","display_name":"Richard G. Baraniuk","orcid":"https://orcid.org/0000-0002-0721-8999"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Richard G. Baraniuk","raw_affiliation_strings":["Dept. Electrical and Computer Engineering, Rice University, Houston, TX#TAB#"],"raw_orcid":"https://orcid.org/0000-0002-0721-8999","affiliations":[{"raw_affiliation_string":"Dept. Electrical and Computer Engineering, Rice University, Houston, TX#TAB#","institution_ids":["https://openalex.org/I74775410"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":22.7889,"has_fulltext":false,"cited_by_count":134,"citation_normalized_percentile":{"value":0.99461049,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"15","issue":"1","first_page":"1959","last_page":"2008"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9983000159263611,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9983000159263611,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9965000152587891,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9934999942779541,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.875232994556427},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7211655378341675},{"id":"https://openalex.org/keywords/learning-analytics","display_name":"Learning analytics","score":0.6044461131095886},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.54997318983078},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5468730926513672},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5442545413970947},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5072755217552185},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.501978874206543},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.475831538438797},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4695594608783722},{"id":"https://openalex.org/keywords/data-analysis","display_name":"Data analysis","score":0.4614710807800293},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.422935426235199},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3473381996154785},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.289145827293396},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15443453192710876}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.875232994556427},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7211655378341675},{"id":"https://openalex.org/C2777648619","wikidata":"https://www.wikidata.org/wiki/Q2845208","display_name":"Learning analytics","level":2,"score":0.6044461131095886},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.54997318983078},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5468730926513672},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5442545413970947},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5072755217552185},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.501978874206543},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.475831538438797},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4695594608783722},{"id":"https://openalex.org/C175801342","wikidata":"https://www.wikidata.org/wiki/Q1988917","display_name":"Data analysis","level":2,"score":0.4614710807800293},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.422935426235199},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3473381996154785},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.289145827293396},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15443453192710876},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:CiteSeerX.psu:10.1.1.715.4749","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.715.4749","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.csl.cornell.edu/%7Estuder/papers/14JMLR-sparfa.pdf","raw_type":"text"},{"id":"mag:2126917700","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1303.5685","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"mag:2126917700","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1303.5685","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[{"score":0.8299999833106995,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":78,"referenced_works":["https://openalex.org/W13474624","https://openalex.org/W15871483","https://openalex.org/W63578216","https://openalex.org/W84528224","https://openalex.org/W124870434","https://openalex.org/W618991135","https://openalex.org/W649466085","https://openalex.org/W1480376833","https://openalex.org/W1488435683","https://openalex.org/W1519271274","https://openalex.org/W1523223036","https://openalex.org/W1535520578","https://openalex.org/W1537529093","https://openalex.org/W1539947443","https://openalex.org/W1557899381","https://openalex.org/W1562748096","https://openalex.org/W1567859451","https://openalex.org/W1569739730","https://openalex.org/W1594781181","https://openalex.org/W1621198417","https://openalex.org/W1648445109","https://openalex.org/W1842230737","https://openalex.org/W1911642898","https://openalex.org/W1949572126","https://openalex.org/W1966382716","https://openalex.org/W1968154520","https://openalex.org/W1969415786","https://openalex.org/W1971040550","https://openalex.org/W1971460272","https://openalex.org/W1986931325","https://openalex.org/W2010161441","https://openalex.org/W2021361347","https://openalex.org/W2027197817","https://openalex.org/W2027866700","https://openalex.org/W2035751541","https://openalex.org/W2039065426","https://openalex.org/W2042950203","https://openalex.org/W2054141820","https://openalex.org/W2060298585","https://openalex.org/W2060430274","https://openalex.org/W2093143832","https://openalex.org/W2100556411","https://openalex.org/W2102081258","https://openalex.org/W2102591969","https://openalex.org/W2105268242","https://openalex.org/W2108806771","https://openalex.org/W2110515480","https://openalex.org/W2112038498","https://openalex.org/W2112447569","https://openalex.org/W2112564774","https://openalex.org/W2117122404","https://openalex.org/W2122606265","https://openalex.org/W2126069482","https://openalex.org/W2127374659","https://openalex.org/W2134767337","https://openalex.org/W2135161976","https://openalex.org/W2136468592","https://openalex.org/W2138145347","https://openalex.org/W2140156116","https://openalex.org/W2146482778","https://openalex.org/W2152872025","https://openalex.org/W2155416760","https://openalex.org/W2159088084","https://openalex.org/W2159094788","https://openalex.org/W2160547390","https://openalex.org/W2161630867","https://openalex.org/W2163395812","https://openalex.org/W2164078599","https://openalex.org/W2181470043","https://openalex.org/W2296319761","https://openalex.org/W2398817920","https://openalex.org/W2407321218","https://openalex.org/W2724459664","https://openalex.org/W2951287198","https://openalex.org/W2963645872","https://openalex.org/W2963857420","https://openalex.org/W3098813406","https://openalex.org/W3201839109"],"related_works":["https://openalex.org/W1562092080","https://openalex.org/W2015040676","https://openalex.org/W650350307","https://openalex.org/W124870434","https://openalex.org/W2054141820","https://openalex.org/W1569739730","https://openalex.org/W2163644476","https://openalex.org/W1959691478","https://openalex.org/W13474624","https://openalex.org/W2127374659","https://openalex.org/W1596401170","https://openalex.org/W2303127372","https://openalex.org/W2100556411","https://openalex.org/W1480376833","https://openalex.org/W2964200481","https://openalex.org/W1523223036","https://openalex.org/W2071159364","https://openalex.org/W1880262756","https://openalex.org/W1535520578","https://openalex.org/W12070778"],"abstract_inverted_index":{"We":[0,77,155],"develop":[1,137],"a":[2,14,21,31,44,51,61,86,101,113,127,139,144,185],"new":[3],"model":[4,39],"and":[5,23,35,72,143,173,189],"algorithms":[6],"for":[7],"machine":[8],"learning-based":[9],"learning":[10,194],"analytics,":[11,25],"which":[12,26],"estimate":[13,27,78],"learner\u2019s":[15],"knowledge":[16],"of":[17,33,55,60,63,88,103,123,130,166,179,197],"the":[18,28,41,47,66,82,104,117,148,164,167,177],"concepts":[19,67],"underlying":[20,64,91],"domain,":[22],"content":[24],"relationships":[29],"among":[30],"collection":[32,87],"questions":[34,105,161],"those":[36],"con-cepts.":[37],"Our":[38],"represents":[40],"probability":[42],"that":[43,111,119,195],"learner":[45],"provides":[46],"correct":[48],"response":[49],"to":[50,85,147,162],"question":[52],"in":[53,69,96],"terms":[54],"three":[56],"factors:":[57],"their":[58],"understanding":[59],"set":[62],"concepts,":[65],"involved":[68],"each":[70,73],"question,":[71],"question\u2019s":[74],"intrinsic":[75],"difficulty.":[76],"these":[79],"factors":[80],"given":[81],"graded":[83],"responses":[84],"questions.":[89],"The":[90,108],"esti-mation":[92],"problem":[93],"is":[94,116,196],"ill-posed":[95],"general,":[97],"especially":[98],"when":[99],"only":[100,126],"subset":[102],"are":[106],"answered.":[107],"key":[109,131],"observation":[110],"enables":[112],"well-posed":[114],"solution":[115,142,146],"fact":[118],"typical":[120],"educational":[121],"domains":[122],"interest":[124],"involve":[125],"small":[128],"number":[129],"concepts.":[132],"Leveraging":[133],"this":[134],"observation,":[135],"we":[136,183],"both":[138],"bi-convex":[140],"maximum-likelihood-based":[141],"Bayesian":[145],"resulting":[149],"SPARse":[150],"Factor":[151],"Analysis":[152],"(SPARFA)":[153],"problem.":[154],"also":[156],"incorporate":[157],"user-defined":[158],"tags":[159],"on":[160],"facilitate":[163],"interpretability":[165],"estimated":[168],"factors.":[169],"Experiments":[170],"with":[171],"synthetic":[172],"real-world":[174],"data":[175],"demonstrate":[176],"efficacy":[178],"our":[180],"approach.":[181],"Finally,":[182],"make":[184],"connection":[186],"between":[187],"SPARFA":[188],"noisy,":[190],"binary-valued":[191],"(1-bit)":[192],"dictionary":[193],"independent":[198],"interest.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":18},{"year":2019,"cited_by_count":13},{"year":2018,"cited_by_count":17},{"year":2017,"cited_by_count":15},{"year":2016,"cited_by_count":14},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":12},{"year":2013,"cited_by_count":5}],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}