{"id":"https://openalex.org/W2165971212","doi":"https://doi.org/10.1145/1835804.1835873","title":"Neighbor query friendly compression of social networks","display_name":"Neighbor query friendly compression of social networks","publication_year":2010,"publication_date":"2010-07-25","ids":{"openalex":"https://openalex.org/W2165971212","doi":"https://doi.org/10.1145/1835804.1835873","mag":"2165971212"},"language":"en","primary_location":{"id":"doi:10.1145/1835804.1835873","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1835804.1835873","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5022612126","display_name":"Hossein Maserrat","orcid":null},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hossein Maserrat","raw_affiliation_strings":["Simon Fraser University, Burnaby, BC, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Simon Fraser University, Burnaby, BC, Canada","institution_ids":["https://openalex.org/I18014758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062247330","display_name":"Jian Pei","orcid":"https://orcid.org/0000-0002-2200-8711"},"institutions":[{"id":"https://openalex.org/I18014758","display_name":"Simon Fraser University","ror":"https://ror.org/0213rcc28","country_code":"CA","type":"education","lineage":["https://openalex.org/I18014758"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jian Pei","raw_affiliation_strings":["Simon Fraser University, Burnaby, BC, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Simon Fraser University, Burnaby, BC, Canada","institution_ids":["https://openalex.org/I18014758"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I18014758"],"apc_list":null,"apc_paid":null,"fwci":5.9827,"has_fulltext":false,"cited_by_count":91,"citation_normalized_percentile":{"value":0.97587096,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"533","last_page":"542"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.998199999332428,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9973000288009644,"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/computer-science","display_name":"Computer science","score":0.7679646015167236},{"id":"https://openalex.org/keywords/social-network","display_name":"Social network (sociolinguistics)","score":0.5380292534828186},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5371838808059692},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.520973265171051},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5113015174865723},{"id":"https://openalex.org/keywords/sublinear-function","display_name":"Sublinear function","score":0.5023066997528076},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.43518105149269104},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.4308200180530548},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.42195022106170654},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2700613737106323},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.2255445122718811},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.22461619973182678},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.15234330296516418},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12401476502418518},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.0696355402469635}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7679646015167236},{"id":"https://openalex.org/C4727928","wikidata":"https://www.wikidata.org/wiki/Q17164759","display_name":"Social network (sociolinguistics)","level":3,"score":0.5380292534828186},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5371838808059692},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.520973265171051},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5113015174865723},{"id":"https://openalex.org/C117160843","wikidata":"https://www.wikidata.org/wiki/Q338652","display_name":"Sublinear function","level":2,"score":0.5023066997528076},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.43518105149269104},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.4308200180530548},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.42195022106170654},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2700613737106323},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.2255445122718811},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.22461619973182678},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.15234330296516418},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12401476502418518},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.0696355402469635},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1835804.1835873","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1835804.1835873","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.182.3595","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.182.3595","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.sfu.ca/%7Ejpei/publications/Social%20Network%20Compression%20KDD%202010.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W85690038","https://openalex.org/W950821216","https://openalex.org/W1517793427","https://openalex.org/W1978024959","https://openalex.org/W1994727615","https://openalex.org/W2018900730","https://openalex.org/W2029852131","https://openalex.org/W2061901927","https://openalex.org/W2079966248","https://openalex.org/W2081193615","https://openalex.org/W2105848461","https://openalex.org/W2112090702","https://openalex.org/W2116207470","https://openalex.org/W2158899306","https://openalex.org/W2161088492","https://openalex.org/W2168924255","https://openalex.org/W3145128584","https://openalex.org/W4285719527","https://openalex.org/W4365806327"],"related_works":["https://openalex.org/W90906771","https://openalex.org/W2018828772","https://openalex.org/W2529185025","https://openalex.org/W2809723425","https://openalex.org/W2052708136","https://openalex.org/W2005302727","https://openalex.org/W3082028334","https://openalex.org/W1973725449","https://openalex.org/W2612632602","https://openalex.org/W2321805087"],"abstract_inverted_index":{"Compressing":[0],"social":[1,12,15,50,55,85],"networks":[2,16,56],"can":[3,26,69,126],"substantially":[4],"facilitate":[5],"mining":[6],"and":[7,130],"advanced":[8],"analysis":[9],"of":[10,40,99,117],"large":[11],"networks.":[13,51],"Preferably,":[14],"should":[17],"be":[18,27,70],"compressed":[19],"in":[20,58,72,133],"a":[21,41,59,91,106,143],"way":[22],"that":[23,64,125],"they":[24],"still":[25,68],"queried":[28],"efficiently":[29],"without":[30],"decompression.":[31],"Arguably,":[32],"neighbor":[33,60,66],"queries,":[34],"which":[35],"search":[36],"for":[37],"all":[38],"neighbors":[39],"query":[42,61],"vertex,":[43],"are":[44],"the":[45,76,111,115,123],"most":[46],"essential":[47],"operations":[48],"on":[49,110,140],"Can":[52],"we":[53,81],"compress":[54],"effectively":[57],"friendly":[62],"manner,":[63],"is,":[65],"queries":[67,132],"answered":[71],"sublinear":[73,134],"time":[74],"using":[75,96],"compression?":[77],"In":[78],"this":[79],"paper,":[80],"develop":[82],"an":[83],"effective":[84],"network":[86],"compression":[87,112],"approach":[88,121],"achieved":[89],"by":[90],"novel":[92],"Eulerian":[93],"data":[94,147],"structure":[95],"multi-position":[97],"linearizations":[98],"directed":[100],"graphs.":[101],"Our":[102],"method":[103],"comes":[104],"with":[105],"nontrivial":[107],"theoretical":[108],"bound":[109],"rate.":[113],"To":[114],"best":[116],"our":[118,120,150],"knowledge,":[119],"is":[122],"first":[124],"answer":[127],"both":[128],"out-neighbor":[129],"in-neighbor":[131],"time.":[135],"An":[136],"extensive":[137],"empirical":[138],"study":[139],"more":[141],"than":[142],"dozen":[144],"benchmark":[145],"real":[146],"sets":[148],"verifies":[149],"design.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":8},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":11},{"year":2013,"cited_by_count":7},{"year":2012,"cited_by_count":8}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
