{"id":"https://openalex.org/W2965592466","doi":"https://doi.org/10.1145/3292500.3332292","title":"Tutorial: Are You My Neighbor?","display_name":"Tutorial: Are You My Neighbor?","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2965592466","doi":"https://doi.org/10.1145/3292500.3332292","mag":"2965592466"},"language":"en","primary_location":{"id":"doi:10.1145/3292500.3332292","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3292500.3332292","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3332292","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3332292","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002755684","display_name":"David C. Anastasiu","orcid":"https://orcid.org/0000-0002-8604-9248"},"institutions":[{"id":"https://openalex.org/I51504820","display_name":"San Jose State University","ror":"https://ror.org/04qyvz380","country_code":"US","type":"education","lineage":["https://openalex.org/I51504820"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"David C. Anastasiu","raw_affiliation_strings":["San Jos\u00e9 State University, San Jose, CA, USA"],"affiliations":[{"raw_affiliation_string":"San Jos\u00e9 State University, San Jose, CA, USA","institution_ids":["https://openalex.org/I51504820"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006581225","display_name":"Huzefa Rangwala","orcid":"https://orcid.org/0000-0003-0435-0035"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Huzefa Rangwala","raw_affiliation_strings":["George Mason University, Fairfax, VA, USA"],"affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, VA, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021211836","display_name":"Andrea Tagarelli","orcid":"https://orcid.org/0000-0002-8142-503X"},"institutions":[{"id":"https://openalex.org/I45204951","display_name":"University of Calabria","ror":"https://ror.org/02rc97e94","country_code":"IT","type":"education","lineage":["https://openalex.org/I45204951"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Andrea Tagarelli","raw_affiliation_strings":["University of Calabria, Rende, Italy"],"affiliations":[{"raw_affiliation_string":"University of Calabria, Rende, Italy","institution_ids":["https://openalex.org/I45204951"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5002755684"],"corresponding_institution_ids":["https://openalex.org/I51504820"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.11776558,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3241","last_page":"3242"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9983000159263611,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.9983000159263611,"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/T11106","display_name":"Data Management and Algorithms","score":0.9968000054359436,"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9944999814033508,"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/bottleneck","display_name":"Bottleneck","score":0.8596744537353516},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7977844476699829},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5675773620605469},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.5176030397415161},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5047584772109985},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4849817752838135},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.4701911211013794},{"id":"https://openalex.org/keywords/nearest-neighbor-search","display_name":"Nearest neighbor search","score":0.4460403621196747},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.44537806510925293},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4137257933616638},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3551650643348694},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.29750704765319824},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.271312415599823},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07946059107780457}],"concepts":[{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.8596744537353516},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7977844476699829},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5675773620605469},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.5176030397415161},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5047584772109985},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4849817752838135},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.4701911211013794},{"id":"https://openalex.org/C116738811","wikidata":"https://www.wikidata.org/wiki/Q608751","display_name":"Nearest neighbor search","level":2,"score":0.4460403621196747},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.44537806510925293},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4137257933616638},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3551650643348694},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.29750704765319824},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.271312415599823},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07946059107780457},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3292500.3332292","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3292500.3332292","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3332292","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:scholarworks.sjsu.edu:computer_eng_pub-1045","is_oa":true,"landing_page_url":"https://scholarworks.sjsu.edu/computer_eng_pub/46","pdf_url":"https://scholarworks.sjsu.edu/cgi/viewcontent.cgi?article=1045&context=computer_eng_pub","source":{"id":"https://openalex.org/S4377196389","display_name":"San Jos\u00e9 State University ScholarWorks (San Jose State University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I51504820","host_organization_name":"San Jose State University","host_organization_lineage":["https://openalex.org/I51504820"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Faculty Publications","raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3292500.3332292","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3292500.3332292","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3292500.3332292","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G670405446","display_name":null,"funder_award_id":"1850557","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2965592466.pdf","grobid_xml":"https://content.openalex.org/works/W2965592466.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1972972498","https://openalex.org/W2022012334","https://openalex.org/W2121710227","https://openalex.org/W2174071288","https://openalex.org/W2296107147","https://openalex.org/W2577223152","https://openalex.org/W2585199909","https://openalex.org/W2737189289","https://openalex.org/W2741196387","https://openalex.org/W2744136723","https://openalex.org/W2761162495","https://openalex.org/W2772756366","https://openalex.org/W2773701625","https://openalex.org/W2792990871","https://openalex.org/W2794909783","https://openalex.org/W2810397803","https://openalex.org/W2904847915","https://openalex.org/W2949278902","https://openalex.org/W2963276349","https://openalex.org/W2963504505","https://openalex.org/W2981964390","https://openalex.org/W3099849870"],"related_works":["https://openalex.org/W2148008870","https://openalex.org/W2381195555","https://openalex.org/W2368606575","https://openalex.org/W4246757943","https://openalex.org/W2132753198","https://openalex.org/W2369874856","https://openalex.org/W2182477562","https://openalex.org/W2792185758","https://openalex.org/W2787484455","https://openalex.org/W2119808169"],"abstract_inverted_index":{"Finding":[0],"nearest":[1,89],"neighbors":[2,45],"is":[3,63],"an":[4],"important":[5],"topic":[6],"that":[7,114],"has":[8,16,46,74],"attracted":[9],"much":[10],"attention":[11],"over":[12],"the":[13,58,72,88,108],"years":[14],"and":[15,27,40],"applications":[17],"in":[18,51,111],"many":[19,83],"fields,":[20],"such":[21],"as":[22],"market":[23],"basket":[24],"analysis,":[25],"plagiarism":[26],"anomaly":[28],"detection,":[29,31],"community":[30],"ligand-based":[32],"virtual":[33],"screening,":[34],"etc.":[35],"As":[36],"data":[37],"are":[38],"easier":[39,41],"to":[42,77],"collect,":[43],"finding":[44],"become":[47],"a":[48,112],"potential":[49],"bottleneck":[50],"analysis":[52],"pipelines.":[53],"Performing":[54],"pairwise":[55],"comparisons":[56],"given":[57],"massive":[59],"datasets":[60],"of":[61,71,87,95],"today":[62],"no":[64],"longer":[65],"feasible.":[66],"The":[67],"high":[68],"computational":[69],"complexity":[70],"task":[73],"led":[75],"researchers":[76],"develop":[78],"approximate":[79],"methods,":[80],"which":[81],"find":[82],"but":[84],"not":[85],"all":[86],"neighbors.":[90],"Yet,":[91],"for":[92],"some":[93],"types":[94],"data,":[96],"efficient":[97],"exact":[98],"solutions":[99],"have":[100],"been":[101],"found":[102],"by":[103],"carefully":[104],"partitioning":[105],"or":[106],"filtering":[107],"search":[109],"space":[110],"way":[113],"avoids":[115],"most":[116],"unnecessary":[117],"comparisons.":[118]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-11T14:59:36.786465","created_date":"2025-10-10T00:00:00"}
