{"id":"https://openalex.org/W4391095609","doi":"https://doi.org/10.1109/bigdata59044.2023.10386642","title":"Diverse Data Expansion with Semi-Supervised k-Determinantal Point Processes","display_name":"Diverse Data Expansion with Semi-Supervised k-Determinantal Point Processes","publication_year":2023,"publication_date":"2023-12-15","ids":{"openalex":"https://openalex.org/W4391095609","doi":"https://doi.org/10.1109/bigdata59044.2023.10386642"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata59044.2023.10386642","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata59044.2023.10386642","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5037160846","display_name":"Simon Johansson","orcid":"https://orcid.org/0000-0001-9139-6378"},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Simon Johansson","raw_affiliation_strings":["Chalmers University of Technology,Department of Computer Science and Engineering,Gothenburg,Sweden","Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chalmers University of Technology,Department of Computer Science and Engineering,Gothenburg,Sweden","institution_ids":["https://openalex.org/I66862912"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076975589","display_name":"Ola Engkvist","orcid":"https://orcid.org/0000-0003-4970-6461"},"institutions":[{"id":"https://openalex.org/I4210143795","display_name":"AstraZeneca (Sweden)","ror":"https://ror.org/04wwrrg31","country_code":"SE","type":"company","lineage":["https://openalex.org/I105036370","https://openalex.org/I4210143795"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Ola Engkvist","raw_affiliation_strings":["Molecular AI, Discovery Sciences, R&#x0026;D AstraZeneca,Gothenburg,Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Molecular AI, Discovery Sciences, R&#x0026;D AstraZeneca,Gothenburg,Sweden","institution_ids":["https://openalex.org/I4210143795"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103015876","display_name":"Morteza Haghir Chehreghani","orcid":"https://orcid.org/0000-0002-2912-7422"},"institutions":[{"id":"https://openalex.org/I66862912","display_name":"Chalmers University of Technology","ror":"https://ror.org/040wg7k59","country_code":"SE","type":"education","lineage":["https://openalex.org/I66862912"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Morteza Haghir Chehreghani","raw_affiliation_strings":["Chalmers University of Technology,Department of Computer Science and Engineering,Gothenburg,Sweden","Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chalmers University of Technology,Department of Computer Science and Engineering,Gothenburg,Sweden","institution_ids":["https://openalex.org/I66862912"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Chalmers University of Technology, Gothenburg, Sweden","institution_ids":["https://openalex.org/I66862912"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057266594","display_name":"Alexander Schliep","orcid":"https://orcid.org/0000-0002-3555-3188"},"institutions":[{"id":"https://openalex.org/I51783024","display_name":"Brandenburg University of Technology Cottbus-Senftenberg","ror":"https://ror.org/02wxx3e24","country_code":"DE","type":"education","lineage":["https://openalex.org/I51783024"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Alexander Schliep","raw_affiliation_strings":["Brandenburg University of Technology Cottbus-Senftenberg,Faculty of Health Sciences,Cottbus,Germany","Faculty of Health Sciences, Brandenburg University of Technology Cottbus-Senftenberg, Cottbus, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Brandenburg University of Technology Cottbus-Senftenberg,Faculty of Health Sciences,Cottbus,Germany","institution_ids":["https://openalex.org/I51783024"]},{"raw_affiliation_string":"Faculty of Health Sciences, Brandenburg University of Technology Cottbus-Senftenberg, Cottbus, Germany","institution_ids":["https://openalex.org/I51783024"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"33","issue":null,"first_page":"5260","last_page":"5265"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.995199978351593,"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/T11106","display_name":"Data Management and Algorithms","score":0.995199978351593,"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/T12176","display_name":"Optimization and Packing Problems","score":0.9553999900817871,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11830","display_name":"Point processes and geometric inequalities","score":0.9466000199317932,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.8547998666763306},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.6995106935501099},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6300702691078186},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6092955470085144},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.6041247844696045},{"id":"https://openalex.org/keywords/point-process","display_name":"Point process","score":0.5882376432418823},{"id":"https://openalex.org/keywords/determinantal-point-process","display_name":"Determinantal point process","score":0.5333437919616699},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5085748434066772},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.46866002678871155},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.42764461040496826},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4209631383419037},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40577131509780884},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.38738858699798584},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3600083589553833},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.334817111492157},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19655227661132812}],"concepts":[{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8547998666763306},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.6995106935501099},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6300702691078186},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6092955470085144},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.6041247844696045},{"id":"https://openalex.org/C88871306","wikidata":"https://www.wikidata.org/wiki/Q7208287","display_name":"Point process","level":2,"score":0.5882376432418823},{"id":"https://openalex.org/C72010251","wikidata":"https://www.wikidata.org/wiki/Q5265688","display_name":"Determinantal point process","level":4,"score":0.5333437919616699},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5085748434066772},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.46866002678871155},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.42764461040496826},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4209631383419037},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40577131509780884},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.38738858699798584},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3600083589553833},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.334817111492157},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19655227661132812},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C64812099","wikidata":"https://www.wikidata.org/wiki/Q176604","display_name":"Random matrix","level":3,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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":2,"locations":[{"id":"doi:10.1109/bigdata59044.2023.10386642","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/bigdata59044.2023.10386642","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},{"id":"pmh:oai:research.chalmers.se:540026","is_oa":false,"landing_page_url":"https://research.chalmers.se/en/publication/540026","pdf_url":null,"source":{"id":"https://openalex.org/S4306402469","display_name":"Chalmers Research (Chalmers University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66862912","host_organization_name":"Chalmers University of Technology","host_organization_lineage":["https://openalex.org/I66862912"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1980073965","https://openalex.org/W1997959284","https://openalex.org/W2101234009","https://openalex.org/W2130623086","https://openalex.org/W2593632281","https://openalex.org/W2891576828","https://openalex.org/W2897429051","https://openalex.org/W2946389721","https://openalex.org/W2950301323","https://openalex.org/W2951079326","https://openalex.org/W2951906369","https://openalex.org/W3103014337","https://openalex.org/W3106190177","https://openalex.org/W3156773840","https://openalex.org/W4221163538","https://openalex.org/W4283820368","https://openalex.org/W4294590201","https://openalex.org/W4389064216","https://openalex.org/W6675354045","https://openalex.org/W6686821501"],"related_works":["https://openalex.org/W4394664801","https://openalex.org/W4288327276","https://openalex.org/W2951327448","https://openalex.org/W3112662864","https://openalex.org/W4381191274","https://openalex.org/W2073583227","https://openalex.org/W2177179288","https://openalex.org/W2962714517","https://openalex.org/W3044388970","https://openalex.org/W4288349944"],"abstract_inverted_index":{"Determinantal":[0],"point":[1,29],"processes":[2,30],"(DPPs)":[3],"have":[4],"become":[5],"prominent":[6],"in":[7,111,119,168],"data":[8],"summarization":[9],"and":[10,81,140,142],"recommender":[11],"system":[12],"tasks":[13],"for":[14],"their":[15],"ability":[16],"to":[17,34,85,105,117],"simultaneously":[18,137],"model":[19],"diversity":[20],"as":[21,23,77],"well":[22],"relevance.":[24],"In":[25,55],"practical":[26],"applications,":[27],"k-Determinantal":[28],"(k-DPPs)":[31],"are":[32,48,103,114],"used":[33],"yield":[35],"a":[36,42,60,70,78,132],"selection":[37,67,161],"of":[38,44,52,63,89],"k":[39],"items":[40,101,110,118],"from":[41],"set":[43,72],"size":[45],"N":[46],"that":[47,102,136],"the":[49,53,64,82,87,90,144,147,158],"most":[50],"representative":[51],"set.":[54],"this":[56],"paper,":[57],"we":[58],"study":[59],"special":[61],"case":[62],"diverse":[65,127,159],"subset":[66,160],"problem":[68,162],"where":[69,157],"fixed":[71],"GO":[73],"is":[74,84,166],"already":[75],"given":[76],"forced":[79,164],"recommendation":[80,91,165],"task":[83],"determine":[86],"remainder":[88],"G1.":[92],"The":[93],"standard":[94],"k-DPP":[95,134],"optimization":[96],"objectives":[97],"here":[98],"can":[99],"suggest":[100],"close":[104,116],"optimal":[106],"when":[107],"considering":[108],"only":[109],"G1,":[112],"but":[113],"arbitrarily":[115],"G0,":[120],"i.e.,":[121],"they":[122],"might":[123],"not":[124],"be":[125],"sufficiently":[126],"w.r.t.":[128],"G0.":[129],"We":[130,150],"explore":[131],"semi-supervised":[133],"objective":[135],"considers":[138],"G0":[139],"G1":[141],"compares":[143],"difference":[145],"between":[146],"two":[148],"recommendations.":[149],"demonstrate":[151],"our":[152],"findings":[153],"using":[154],"multiple":[155],"examples":[156],"with":[163],"important":[167],"practice.":[169]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
