{"id":"https://openalex.org/W2171013708","doi":"https://doi.org/10.1145/2806416.2806515","title":"Weighted Similarity Estimation in Data Streams","display_name":"Weighted Similarity Estimation in Data Streams","publication_year":2015,"publication_date":"2015-10-17","ids":{"openalex":"https://openalex.org/W2171013708","doi":"https://doi.org/10.1145/2806416.2806515","mag":"2171013708"},"language":"en","primary_location":{"id":"doi:10.1145/2806416.2806515","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2806416.2806515","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM International on Conference on Information and Knowledge Management","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/A5069687493","display_name":"Konstantin Kutzkov","orcid":"https://orcid.org/0000-0002-7334-6868"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Konstantin Kutzkov","raw_affiliation_strings":["NEC Laboratories Europe, Heidelberg, Germany"],"affiliations":[{"raw_affiliation_string":"NEC Laboratories Europe, Heidelberg, Germany","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062100859","display_name":"Mohamed Ahmed","orcid":"https://orcid.org/0000-0002-3325-0204"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohamed Ahmed","raw_affiliation_strings":["NEC Laboratories Europe, Heidelberg, Germany"],"affiliations":[{"raw_affiliation_string":"NEC Laboratories Europe, Heidelberg, Germany","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039854862","display_name":"Sofia Nikitaki","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sofia Nikitaki","raw_affiliation_strings":["NEC Laboratories Europe, Heidelberg, Germany"],"affiliations":[{"raw_affiliation_string":"NEC Laboratories Europe, Heidelberg, Germany","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5069687493"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2943,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.85975519,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1051","last_page":"1060"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12761","display_name":"Data Stream Mining Techniques","score":0.9969000220298767,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9969000220298767,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.8099790811538696},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.7990460395812988},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7894864678382874},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.7548080682754517},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6318745017051697},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6021161675453186},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.5914013385772705},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5524482131004333},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.46309661865234375},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.43264269828796387},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3622918725013733},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3520912528038025},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.23128953576087952},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09750872850418091}],"concepts":[{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.8099790811538696},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.7990460395812988},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7894864678382874},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7548080682754517},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6318745017051697},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6021161675453186},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.5914013385772705},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5524482131004333},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.46309661865234375},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.43264269828796387},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3622918725013733},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3520912528038025},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.23128953576087952},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09750872850418091},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2806416.2806515","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2806416.2806515","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 24th ACM International on Conference on Information and Knowledge Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7099999785423279,"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":32,"referenced_works":["https://openalex.org/W1493892051","https://openalex.org/W1499558210","https://openalex.org/W1502916507","https://openalex.org/W1885689371","https://openalex.org/W1972525637","https://openalex.org/W1984630650","https://openalex.org/W1991800036","https://openalex.org/W2002290767","https://openalex.org/W2004110412","https://openalex.org/W2012833704","https://openalex.org/W2040559836","https://openalex.org/W2048779798","https://openalex.org/W2052207834","https://openalex.org/W2061820396","https://openalex.org/W2073926352","https://openalex.org/W2080745194","https://openalex.org/W2081193615","https://openalex.org/W2084527756","https://openalex.org/W2086694417","https://openalex.org/W2107443258","https://openalex.org/W2109742433","https://openalex.org/W2113853816","https://openalex.org/W2122056984","https://openalex.org/W2128891547","https://openalex.org/W2129713756","https://openalex.org/W2129930407","https://openalex.org/W2133266261","https://openalex.org/W2140431670","https://openalex.org/W2169054943","https://openalex.org/W2188225224","https://openalex.org/W2295428206","https://openalex.org/W6629956336"],"related_works":["https://openalex.org/W2348159088","https://openalex.org/W2076210137","https://openalex.org/W2893089803","https://openalex.org/W2576320324","https://openalex.org/W2001231889","https://openalex.org/W2402445420","https://openalex.org/W2945202055","https://openalex.org/W2301206649","https://openalex.org/W1773619406","https://openalex.org/W2171013708"],"abstract_inverted_index":{"Similarity":[0],"computation":[1],"between":[2],"pairs":[3],"of":[4,20,48],"objects":[5],"is":[6],"often":[7],"a":[8],"bottleneck":[9],"in":[10,29,37,51],"many":[11],"applications":[12,24],"that":[13],"have":[14],"to":[15],"deal":[16],"with":[17],"massive":[18],"volumes":[19],"data.":[21],"Motivated":[22],"by":[23],"such":[25],"as":[26],"collaborative":[27],"filtering":[28],"large-scale":[30],"recommender":[31],"systems,":[32],"and":[33],"influence":[34],"probabilities":[35],"learning":[36],"social":[38],"networks,":[39],"we":[40],"present":[41],"new":[42],"randomized":[43],"algorithms":[44],"for":[45],"the":[46],"estimation":[47],"weighted":[49],"similarity":[50],"data":[52],"streams.":[53]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}