{"id":"https://openalex.org/W134212334","doi":"https://doi.org/10.3233/978-1-58603-891-5-261","title":"Modeling Collaborative Similarity with the Signed Resistance Distance Kernel","display_name":"Modeling Collaborative Similarity with the Signed Resistance Distance Kernel","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W134212334","doi":"https://doi.org/10.3233/978-1-58603-891-5-261","mag":"134212334"},"language":"en","primary_location":{"id":"doi:10.3233/978-1-58603-891-5-261","is_oa":false,"landing_page_url":"https://doi.org/10.3233/978-1-58603-891-5-261","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","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":null,"display_name":"Kunegis Jérôme","orcid":null},"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":"Kunegis Jérôme","raw_affiliation_strings":["DAI-Labor, Technische Universit\u00e4t Berlin, Germany. E-mail: kunegis@dai-lab.de#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DAI-Labor, Technische Universit\u00e4t Berlin, Germany. E-mail: kunegis@dai-lab.de#TAB#","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062673118","display_name":"Stephan Schmidt","orcid":"https://orcid.org/0000-0002-4998-1167"},"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":"Schmidt Stephan","raw_affiliation_strings":["DAI-Labor, Technische Universit\u00e4t Berlin, Germany. E-mail: stephan.schmidt@dai-lab.de#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DAI-Labor, Technische Universit\u00e4t Berlin, Germany. E-mail: stephan.schmidt@dai-lab.de#TAB#","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Albayrak Şahin","orcid":null},"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":"Albayrak Şahin","raw_affiliation_strings":["DAI-Labor, Technische Universit\u00e4t Berlin, Germany. E-mail: sahin@dai-lab.de#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DAI-Labor, Technische Universit\u00e4t Berlin, Germany. E-mail: sahin@dai-lab.de#TAB#","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003875445","display_name":"Christian Bauckhage","orcid":"https://orcid.org/0000-0001-6615-2128"},"institutions":[{"id":"https://openalex.org/I4210093367","display_name":"Deutsche Telekom (Germany)","ror":"https://ror.org/00m8prc86","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210093367"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bauckhage Christian","raw_affiliation_strings":["Telekom Laboratories, Berlin, Germany. E-mail: christian.bauckhage@telekom.de#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Telekom Laboratories, Berlin, Germany. E-mail: christian.bauckhage@telekom.de#TAB#","institution_ids":["https://openalex.org/I4210093367"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072183562","display_name":"Martin Mehlitz","orcid":null},"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":"Mehlitz Martin","raw_affiliation_strings":["DAI-Labor, Technische Universit\u00e4t Berlin, Germany. E-mail: martin.mehlitz@googlemail.com#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DAI-Labor, Technische Universit\u00e4t Berlin, Germany. E-mail: martin.mehlitz@googlemail.com#TAB#","institution_ids":["https://openalex.org/I4577782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.9188,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.86674528,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9890000224113464,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9868999719619751,"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/similarity","display_name":"Similarity (geometry)","score":0.661395788192749},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.536949634552002},{"id":"https://openalex.org/keywords/signed-graph","display_name":"Signed graph","score":0.49024492502212524},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4433125853538513},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.41813182830810547},{"id":"https://openalex.org/keywords/resistance","display_name":"Resistance (ecology)","score":0.41070759296417236},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3430343270301819},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.22589069604873657},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.08703446388244629},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.03211599588394165}],"concepts":[{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.661395788192749},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.536949634552002},{"id":"https://openalex.org/C2779773260","wikidata":"https://www.wikidata.org/wiki/Q11246292","display_name":"Signed graph","level":3,"score":0.49024492502212524},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4433125853538513},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.41813182830810547},{"id":"https://openalex.org/C57473165","wikidata":"https://www.wikidata.org/wiki/Q7315604","display_name":"Resistance (ecology)","level":2,"score":0.41070759296417236},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3430343270301819},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.22589069604873657},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.08703446388244629},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.03211599588394165},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/978-1-58603-891-5-261","is_oa":false,"landing_page_url":"https://doi.org/10.3233/978-1-58603-891-5-261","pdf_url":null,"source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W56396525","https://openalex.org/W1566698804","https://openalex.org/W1781055995","https://openalex.org/W1971040550","https://openalex.org/W2018605660","https://openalex.org/W2049455633","https://openalex.org/W2085937320","https://openalex.org/W2110325612","https://openalex.org/W2124591829","https://openalex.org/W2139555631","https://openalex.org/W2142124258","https://openalex.org/W2146376298","https://openalex.org/W2155106456","https://openalex.org/W2161984370","https://openalex.org/W2168108570"],"related_works":["https://openalex.org/W2803645288","https://openalex.org/W4312030669","https://openalex.org/W2951273415","https://openalex.org/W3080247920","https://openalex.org/W2440517957","https://openalex.org/W3024241193","https://openalex.org/W1928585071","https://openalex.org/W4224985635","https://openalex.org/W590006546","https://openalex.org/W3102545889"],"abstract_inverted_index":{"We":[0,46,77,115],"extend":[1],"the":[2,7,48,64,80,90,94,98,108,112,124,136],"resistance":[3,25,61,68,82],"distance":[4,26,69,83],"kernel":[5,30,70,84,133],"to":[6,20,74,103,119],"domain":[8],"of":[9,38,52,93,97,111],"signed":[10,60,81],"dissimilarity":[11],"values,":[12],"and":[13,128],"show":[14,78,129],"how":[15,130],"it":[16],"can":[17,85,134],"be":[18,86],"applied":[19],"collaborative":[21,55,120],"rating":[22,56,100,121,141],"prediction.":[23,142],"The":[24],"is":[27,72],"a":[28,39,53],"graph":[29,40],"inspired":[31],"by":[32],"electrical":[33,44],"network":[34],"models":[35],"where":[36],"edges":[37],"are":[41],"interpreted":[42],"as":[43],"resistances.":[45],"model":[47],"similarity":[49],"between":[50],"users":[51],"large":[54],"database":[57],"using":[58,89],"this":[59,117],"distance,":[62],"generalizing":[63],"previously":[65],"known":[66],"regular":[67],"which":[71],"limited":[73],"nonnegative":[75],"values.":[76],"that":[79],"computed":[87],"effectively":[88],"Moore-Penrose":[91],"pseudoinverse":[92],"Laplacian":[95,113],"matrix":[96],"bipartite":[99],"graph,":[101],"leading":[102],"fast":[104],"computation":[105],"based":[106],"on":[107,123],"eigenvalue":[109],"decomposition":[110],"matrix.":[114],"apply":[116],"technique":[118],"prediction":[122],"Netflix":[125],"Prize":[126],"corpus,":[127],"our":[131],"new":[132],"replace":[135],"traditional":[137],"Pearson":[138],"correlation":[139],"for":[140]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2016-06-24T00:00:00"}