{"id":"https://openalex.org/W2952179887","doi":"https://doi.org/10.1145/3292500.3330847","title":"Predicting Path Failure In Time-Evolving Graphs","display_name":"Predicting Path Failure In Time-Evolving Graphs","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2952179887","doi":"https://doi.org/10.1145/3292500.3330847","mag":"2952179887"},"language":"en","primary_location":{"id":"doi:10.1145/3292500.3330847","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330847","pdf_url":null,"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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100613330","display_name":"Jia Li","orcid":"https://orcid.org/0000-0003-2900-9108"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jia Li","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022714894","display_name":"Zhichao Han","orcid":"https://orcid.org/0000-0003-2195-5706"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhichao Han","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085614235","display_name":"Hong Cheng","orcid":"https://orcid.org/0000-0002-4943-9060"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Cheng","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103250546","display_name":"Jiao Su","orcid":"https://orcid.org/0000-0003-2610-6068"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiao Su","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103134726","display_name":"Pengyun Wang","orcid":"https://orcid.org/0009-0001-9696-6947"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengyun Wang","raw_affiliation_strings":["Noah's Ark Lab, Huawei Technologies, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Noah's Ark Lab, Huawei Technologies, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100374699","display_name":"Jianfeng Zhang","orcid":"https://orcid.org/0000-0001-7218-6383"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Zhang","raw_affiliation_strings":["Noah's Ark Lab, Huawei Technologies, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Noah's Ark Lab, Huawei Technologies, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009221204","display_name":"Lujia Pan","orcid":"https://orcid.org/0000-0002-8988-4740"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lujia Pan","raw_affiliation_strings":["Noah's Ark Lab, Huawei Technologies, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Noah's Ark Lab, Huawei Technologies, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100613330"],"corresponding_institution_ids":["https://openalex.org/I177725633"],"apc_list":null,"apc_paid":null,"fwci":8.8969,"has_fulltext":false,"cited_by_count":124,"citation_normalized_percentile":{"value":0.98238072,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1279","last_page":"1289"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11598","display_name":"Internet Traffic Analysis and Secure E-voting","score":0.9976999759674072,"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":0.996999979019165,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7727679014205933},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5440248250961304},{"id":"https://openalex.org/keywords/average-path-length","display_name":"Average path length","score":0.5440125465393066},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.525585949420929},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.5119568109512329},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.49175241589546204},{"id":"https://openalex.org/keywords/fast-path","display_name":"Fast path","score":0.47832608222961426},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4761531352996826},{"id":"https://openalex.org/keywords/longest-path-problem","display_name":"Longest path problem","score":0.45138105750083923},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3448294401168823},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32163456082344055},{"id":"https://openalex.org/keywords/shortest-path-problem","display_name":"Shortest path problem","score":0.22704178094863892},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.13569945096969604}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7727679014205933},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5440248250961304},{"id":"https://openalex.org/C91886571","wikidata":"https://www.wikidata.org/wiki/Q432520","display_name":"Average path length","level":4,"score":0.5440125465393066},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.525585949420929},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.5119568109512329},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.49175241589546204},{"id":"https://openalex.org/C32638748","wikidata":"https://www.wikidata.org/wiki/Q5437051","display_name":"Fast path","level":4,"score":0.47832608222961426},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4761531352996826},{"id":"https://openalex.org/C1465435","wikidata":"https://www.wikidata.org/wiki/Q2916352","display_name":"Longest path problem","level":4,"score":0.45138105750083923},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3448294401168823},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32163456082344055},{"id":"https://openalex.org/C22590252","wikidata":"https://www.wikidata.org/wiki/Q1058754","display_name":"Shortest path problem","level":3,"score":0.22704178094863892},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.13569945096969604},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3292500.3330847","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3330847","pdf_url":null,"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:repository.hkust.edu.hk:1783.1-161369","is_oa":false,"landing_page_url":"http://repository.hkust.edu.hk/ir/Record/1783.1-161369","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1535760514","display_name":null,"funder_award_id":"CUHK 14205618","funder_id":"https://openalex.org/F4320321592","funder_display_name":"Research Grants Council, University Grants Committee"},{"id":"https://openalex.org/G7999985857","display_name":null,"funder_award_id":"Research and Development Fund","funder_id":"https://openalex.org/F4320322183","funder_display_name":"Huawei Technologies"}],"funders":[{"id":"https://openalex.org/F4320321592","display_name":"Research Grants Council, University Grants Committee","ror":"https://ror.org/00djwmt25"},{"id":"https://openalex.org/F4320322183","display_name":"Huawei Technologies","ror":"https://ror.org/00cmhce21"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W116902681","https://openalex.org/W1677182931","https://openalex.org/W1979406157","https://openalex.org/W1990867478","https://openalex.org/W2008056655","https://openalex.org/W2040297119","https://openalex.org/W2064675550","https://openalex.org/W2146377002","https://openalex.org/W2154851992","https://openalex.org/W2187089797","https://openalex.org/W2405761224","https://openalex.org/W2519887557","https://openalex.org/W2528639018","https://openalex.org/W2551441958","https://openalex.org/W2592735969","https://openalex.org/W2597655663","https://openalex.org/W2604314403","https://openalex.org/W2605174772","https://openalex.org/W2913015533","https://openalex.org/W2949888546","https://openalex.org/W2963358464","https://openalex.org/W3103720336","https://openalex.org/W3104097132"],"related_works":["https://openalex.org/W830396839","https://openalex.org/W3196508834","https://openalex.org/W2132921321","https://openalex.org/W2490317825","https://openalex.org/W2116465486","https://openalex.org/W2101572961","https://openalex.org/W2129550502","https://openalex.org/W1759713541","https://openalex.org/W2020255949","https://openalex.org/W1995629993"],"abstract_inverted_index":{"In":[0,61],"this":[1],"paper":[2],"we":[3,72,146],"use":[4],"a":[5,11,30,46,54,74,94,114,136,141],"time-evolving":[6,31],"graph":[7,14,69,91],"which":[8,33],"consists":[9],"of":[10,13,127,150,164],"sequence":[12],"snapshots":[15,92],"over":[16],"time":[17],"to":[18,63,103,124,152],"model":[19],"many":[20,35],"real-world":[21,38,137],"networks.":[22],"We":[23,111],"study":[24],"the":[25,58,65,148,162],"path":[26,43,51,116,121,157,167],"classification":[27],"problem":[28],"in":[29,37,45,53,57,144,156],"graph,":[32],"has":[34],"applications":[36],"scenarios,":[39],"for":[40],"example,":[41],"predicting":[42,50],"failure":[44,158],"telecommunication":[47,138],"network":[48,56,78,139,143],"and":[49,68,99,108,140,160],"congestion":[52],"traffic":[55,142],"near":[59],"future.":[60],"order":[62],"capture":[64],"temporal":[66,87],"dependency":[67,88],"structure":[70],"dynamics,":[71],"design":[73],"novel":[75],"deep":[76],"neural":[77],"named":[79,119],"Long":[80],"Short-Term":[81],"Memory":[82],"R-GCN":[83],"(LRGCN).":[84],"LRGCN":[85,151],"considers":[86],"between":[89],"time-adjacent":[90],"as":[93],"special":[95],"relation":[96],"with":[97],"memory,":[98],"uses":[100],"relational":[101],"GCN":[102],"jointly":[104],"process":[105],"both":[106],"intra-time":[107],"inter-time":[109],"relations.":[110],"also":[112],"propose":[113],"new":[115],"representation":[117],"method":[118],"self-attentive":[120],"embedding":[122],"(SAPE),":[123],"embed":[125],"paths":[126],"arbitrary":[128],"length":[129],"into":[130],"fixed-length":[131],"vectors.":[132],"Through":[133],"experiments":[134],"on":[135,166],"California,":[145],"demonstrate":[147],"superiority":[149],"other":[153],"competing":[154],"methods":[155],"prediction,":[159],"prove":[161],"effectiveness":[163],"SAPE":[165],"representation.":[168]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":19},{"year":2023,"cited_by_count":31},{"year":2022,"cited_by_count":23},{"year":2021,"cited_by_count":23},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
