{"id":"https://openalex.org/W4392384843","doi":"https://doi.org/10.1145/3616855.3635694","title":"Temporal Graph Analysis with TGX","display_name":"Temporal Graph Analysis with TGX","publication_year":2024,"publication_date":"2024-03-04","ids":{"openalex":"https://openalex.org/W4392384843","doi":"https://doi.org/10.1145/3616855.3635694"},"language":"en","primary_location":{"id":"doi:10.1145/3616855.3635694","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3616855.3635694","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Web Search 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/A5055825507","display_name":"Razieh Shirzadkhani","orcid":"https://orcid.org/0009-0000-7328-3177"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Razieh Shirzadkhani","raw_affiliation_strings":["McGill University & Mila, Montreal, Canada"],"raw_orcid":"https://orcid.org/0009-0000-7328-3177","affiliations":[{"raw_affiliation_string":"McGill University & Mila, Montreal, Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105038937","display_name":"Shenyang Huang","orcid":"https://orcid.org/0000-0002-4526-7097"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Shenyang Huang","raw_affiliation_strings":["McGill University & Mila, Montreal, Canada"],"raw_orcid":"https://orcid.org/0000-0002-4526-7097","affiliations":[{"raw_affiliation_string":"McGill University & Mila, Montreal, Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093887433","display_name":"Elahe Kooshafar","orcid":"https://orcid.org/0009-0008-1170-4683"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Elahe Kooshafar","raw_affiliation_strings":["McGill University & Mila, Montreal, Canada"],"raw_orcid":"https://orcid.org/0009-0008-1170-4683","affiliations":[{"raw_affiliation_string":"McGill University & Mila, Montreal, Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043159673","display_name":"Reihaneh Rabbany","orcid":"https://orcid.org/0000-0003-2348-0353"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Reihaneh Rabbany","raw_affiliation_strings":["McGill University & Mila, Montreal, Canada"],"raw_orcid":"https://orcid.org/0000-0003-2348-0353","affiliations":[{"raw_affiliation_string":"McGill University & Mila, Montreal, Canada","institution_ids":["https://openalex.org/I5023651"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021512115","display_name":"Farimah Poursafaei","orcid":"https://orcid.org/0009-0006-6785-3253"},"institutions":[{"id":"https://openalex.org/I5023651","display_name":"McGill University","ror":"https://ror.org/01pxwe438","country_code":"CA","type":"education","lineage":["https://openalex.org/I5023651"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Farimah Poursafaei","raw_affiliation_strings":["McGill University & Mila, Montreal, Canada"],"raw_orcid":"https://orcid.org/0009-0006-6785-3253","affiliations":[{"raw_affiliation_string":"McGill University & Mila, Montreal, Canada","institution_ids":["https://openalex.org/I5023651"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I5023651"],"apc_list":null,"apc_paid":null,"fwci":0.9324,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.65423729,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1086","last_page":"1089"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9976000189781189,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9976000189781189,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","score":0.9843000173568726,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7320840358734131},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.5535238981246948},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.503304660320282},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.41656693816185},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3696352243423462},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.23114001750946045},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.13533803820610046}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7320840358734131},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.5535238981246948},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.503304660320282},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.41656693816185},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3696352243423462},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.23114001750946045},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.13533803820610046},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3616855.3635694","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3616855.3635694","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 17th ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320309949","display_name":"Canadian Institute for Advanced Research","ror":"https://ror.org/01sdtdd95"},{"id":"https://openalex.org/F4320332195","display_name":"Samsung","ror":"https://ror.org/04w3jy968"},{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"},{"id":"https://openalex.org/F4320334841","display_name":"Fonds de recherche du Qu\u00e9bec \u2013 Nature et technologies","ror":"https://ror.org/00b9f9778"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":6,"referenced_works":["https://openalex.org/W3019863187","https://openalex.org/W3026076535","https://openalex.org/W3210361503","https://openalex.org/W4286750969","https://openalex.org/W4300978465","https://openalex.org/W6844651315"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2341492732","https://openalex.org/W3187193180","https://openalex.org/W106542691","https://openalex.org/W1699080303","https://openalex.org/W4297799326","https://openalex.org/W3116064965","https://openalex.org/W4287027380","https://openalex.org/W3193760048"],"abstract_inverted_index":{"Real-world":[0],"networks,":[1,187,189],"with":[2,107],"their":[3],"evolving":[4,60,130],"relations,":[5],"are":[6,16],"best":[7],"captured":[8],"as":[9,77,79,96,152],"temporal":[10,27,45,99,149,175],"graphs.":[11,61],"However,":[12],"existing":[13],"software":[14],"libraries":[15],"largely":[17],"designed":[18,41],"for":[19,42,52,170],"static":[20],"graphs":[21,28,100,176],"where":[22],"the":[23,84,129,139,146,172],"dynamic":[24],"nature":[25],"of":[26,44,59,98,122,132,148,174],"is":[29,166,207],"ignored.":[30],"Bridging":[31],"this":[32],"gap,":[33],"we":[34],"introduce":[35],"TGX,":[36],"a":[37,119,167],"Python":[38],"package":[39,140,165],"specially":[40],"analysis":[43,58,116],"networks":[46],"that":[47],"encompasses":[48],"an":[49],"automated":[50],"pipeline":[51],"data":[53,55,88,92],"loading,":[54,89],"processing,":[56],"and":[57,69,101,128,134,157,177,190,199],"TGX":[62,90,113,164,201,206],"provides":[63],"access":[64],"to":[65,104,196],"eleven":[66],"built-in":[67],"datasets":[68,76,82],"eight":[70],"external":[71],"Temporal":[72,153,158],"Graph":[73],"Benchmark":[74],"(TGB)":[75],"well":[78],"any":[80],"novel":[81],"in":[83,181],".csv":[85],"format.":[86],"Beyond":[87],"facilitates":[91],"processing":[93],"functionalities":[94],"such":[95,151],"discretization":[97],"node":[102,126],"sub-sampling":[103],"accelerate":[105],"working":[106],"larger":[108],"datasets.":[109],"For":[110],"comprehensive":[111],"investigation,":[112],"offers":[114],"network":[115],"by":[117],"providing":[118],"diverse":[120],"set":[121],"measures,":[123],"including":[124],"average":[125],"degree":[127],"number":[131],"nodes":[133],"edges":[135],"per":[136],"timestamp.":[137],"Additionally,":[138],"consolidates":[141],"meaningful":[142],"visualization":[143],"plots":[144],"indicating":[145],"evolution":[147],"patterns,":[150],"Edge":[154,159],"Appearance":[155],"(TEA)":[156],"Traffic":[160],"(TET)":[161],"plots.":[162],"The":[163],"robust":[168],"tool":[169],"examining":[171],"features":[173],"can":[178],"be":[179],"used":[180],"various":[182],"areas":[183],"like":[184],"studying":[185],"social":[186],"citation":[188],"tracking":[191],"user":[192],"interactions.":[193],"We":[194],"plan":[195],"continuously":[197],"support":[198],"update":[200],"based":[202],"on":[203],"community":[204],"feedback.":[205],"publicly":[208],"available":[209],"on:":[210],"https://github.com/ComplexData-MILA/TGX.":[211]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}