{"id":"https://openalex.org/W2007636657","doi":"https://doi.org/10.1145/2441776.2441933","title":"User-centric evaluation of a K-furthest neighbor collaborative filtering recommender algorithm","display_name":"User-centric evaluation of a K-furthest neighbor collaborative filtering recommender algorithm","publication_year":2013,"publication_date":"2013-02-22","ids":{"openalex":"https://openalex.org/W2007636657","doi":"https://doi.org/10.1145/2441776.2441933","mag":"2007636657"},"language":"en","primary_location":{"id":"doi:10.1145/2441776.2441933","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2441776.2441933","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 conference on Computer supported cooperative work","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/A5040472816","display_name":"Alan Said","orcid":"https://orcid.org/0000-0002-2929-0529"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Alan Said","raw_affiliation_strings":["Technische Universit\u00e4t Berlin, Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technische Universit\u00e4t Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103804537","display_name":"Ben Fields","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ben Fields","raw_affiliation_strings":["Musicmetric, Semetric Ltd., London, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Musicmetric, Semetric Ltd., London, UK","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080362374","display_name":"Brijnesh J. Jain","orcid":"https://orcid.org/0000-0003-1844-6687"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brijnesh J. Jain","raw_affiliation_strings":["Berlin University of Technology, Berlin, Germany","Berlin University of Technology , Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Berlin University of Technology, Berlin, Germany","institution_ids":[]},{"raw_affiliation_string":"Berlin University of Technology , Berlin, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089847337","display_name":"\u015eahin Albayrak","orcid":"https://orcid.org/0000-0001-5092-4584"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sahin Albayrak","raw_affiliation_strings":["Technical University of Berlin, Berlin, Germany","Technical University of Berlin, Berlin (Germany)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]},{"raw_affiliation_string":"Technical University of Berlin, Berlin (Germany)","institution_ids":["https://openalex.org/I4577782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":35.1198,"has_fulltext":false,"cited_by_count":119,"citation_normalized_percentile":{"value":0.99638436,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1399","last_page":"1408"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9797000288963318,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T13274","display_name":"Expert finding and Q&A systems","score":0.9743000268936157,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/collaborative-filtering","display_name":"Collaborative filtering","score":0.8948830962181091},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.8360480070114136},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8247305154800415},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.6814390420913696},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5703717470169067},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5591778755187988},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4662211239337921},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4611971378326416},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3638029396533966},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35742974281311035}],"concepts":[{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.8948830962181091},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8360480070114136},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8247305154800415},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.6814390420913696},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5703717470169067},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5591778755187988},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4662211239337921},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4611971378326416},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3638029396533966},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35742974281311035},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2441776.2441933","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2441776.2441933","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2013 conference on Computer supported cooperative work","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320324094","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40"},{"id":"https://openalex.org/F4320332688","display_name":"University of California, Irvine","ror":"https://ror.org/04gyf1771"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1483715664","https://openalex.org/W1488971269","https://openalex.org/W1491742575","https://openalex.org/W1547244403","https://openalex.org/W1774663064","https://openalex.org/W1832221731","https://openalex.org/W1971040550","https://openalex.org/W2020631728","https://openalex.org/W2040559836","https://openalex.org/W2044277341","https://openalex.org/W2045453095","https://openalex.org/W2049670925","https://openalex.org/W2096250234","https://openalex.org/W2101019781","https://openalex.org/W2110325612","https://openalex.org/W2111094216","https://openalex.org/W2122111042","https://openalex.org/W2125330369","https://openalex.org/W2128629010","https://openalex.org/W2138825227","https://openalex.org/W2155893006","https://openalex.org/W2155912844","https://openalex.org/W2159155347","https://openalex.org/W2162111811","https://openalex.org/W2166938806","https://openalex.org/W2501518699","https://openalex.org/W2602645338","https://openalex.org/W2622684336","https://openalex.org/W2950332743","https://openalex.org/W3035787931"],"related_works":["https://openalex.org/W2772628444","https://openalex.org/W2735929803","https://openalex.org/W4220714703","https://openalex.org/W1484355083","https://openalex.org/W3008845055","https://openalex.org/W2098758514","https://openalex.org/W4376854386","https://openalex.org/W2202724490","https://openalex.org/W2508671622","https://openalex.org/W2556532874"],"abstract_inverted_index":{"Collaborative":[0],"filtering":[1],"recommender":[2,82],"systems":[3],"often":[4],"use":[5],"nearest":[6],"neighbor":[7,81,101],"methods":[8],"to":[9,24,70],"identify":[10,25,71],"candidate":[11],"items.":[12],"In":[13],"this":[14],"paper":[15],"we":[16],"present":[17],"an":[18,65],"inverted":[19],"neighborhood":[20],"model,":[21],"k-Furthest":[22],"Neighbors,":[23],"less":[26],"ordinary":[27],"neighborhoods":[28],"for":[29],"the":[30,51,76,98,106,110,114,121,124],"purpose":[31],"of":[32,75,113,123],"creating":[33],"more":[34],"diverse":[35],"recommendations.":[36],"The":[37],"approach":[38],"is":[39,53,83,103],"evaluated":[40],"two-fold,":[41],"once":[42,63],"in":[43,88,105,120],"a":[44,58,86],"traditional":[45,107],"information":[46],"retrieval":[47],"evaluation":[48,90,93,108],"setting":[49],"where":[50],"model":[52,102],"trained":[54],"and":[55,62],"validated":[56],"on":[57],"split":[59],"train/test":[60],"set,":[61],"through":[64],"online":[66],"user":[67,125],"study":[68],"(N=132)":[69],"users'":[72],"perceived":[73,111],"quality":[74],"recommender.":[77],"A":[78],"standard":[79],"k-nearest":[80],"used":[84],"as":[85],"baseline":[87],"both":[89],"settings.":[91],"Our":[92],"shows":[94,116],"that":[95],"even":[96],"though":[97],"proposed":[99],"furthest":[100],"outperformed":[104],"setting,":[109],"usefulness":[112],"algorithm":[115],"no":[117],"significant":[118],"difference":[119],"results":[122],"study.":[126]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":20},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":15},{"year":2015,"cited_by_count":11},{"year":2014,"cited_by_count":9},{"year":2013,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
