{"id":"https://openalex.org/W4385567963","doi":"https://doi.org/10.1145/3580305.3599415","title":"LightPath: Lightweight and Scalable Path Representation Learning","display_name":"LightPath: Lightweight and Scalable Path Representation Learning","publication_year":2023,"publication_date":"2023-08-04","ids":{"openalex":"https://openalex.org/W4385567963","doi":"https://doi.org/10.1145/3580305.3599415"},"language":"en","primary_location":{"id":"doi:10.1145/3580305.3599415","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599415","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and 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/A5054708051","display_name":"Bin Yang","orcid":"https://orcid.org/0000-0001-7819-2290"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":true,"raw_author_name":"Sean Bin Yang","raw_affiliation_strings":["Aalborg University, Aalborg, Denmark"],"affiliations":[{"raw_affiliation_string":"Aalborg University, Aalborg, Denmark","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020559625","display_name":"Jilin Hu","orcid":"https://orcid.org/0000-0002-7739-7769"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jilin Hu","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084021933","display_name":"Chenjuan Guo","orcid":"https://orcid.org/0000-0002-4516-4637"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenjuan Guo","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072309548","display_name":"Bin Yang","orcid":"https://orcid.org/0000-0002-1658-1079"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Yang","raw_affiliation_strings":["East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029380368","display_name":"Christian S. Jensen","orcid":"https://orcid.org/0000-0002-9697-7670"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Christian S. Jensen","raw_affiliation_strings":["Aalborg University, Aalborg, Denmark"],"affiliations":[{"raw_affiliation_string":"Aalborg University, Aalborg, Denmark","institution_ids":["https://openalex.org/I891191580"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5054708051"],"corresponding_institution_ids":["https://openalex.org/I891191580"],"apc_list":null,"apc_paid":null,"fwci":2.7526,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.89387238,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2999","last_page":"3010"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9986000061035156,"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":0.9986000061035156,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9896000027656555,"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/T11106","display_name":"Data Management and Algorithms","score":0.9807000160217285,"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/scalability","display_name":"Scalability","score":0.8558000326156616},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8038155436515808},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.646848738193512},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.5865781307220459},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5668815970420837},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.5469874739646912},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5361143946647644},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5242781043052673},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4637959599494934},{"id":"https://openalex.org/keywords/resource-consumption","display_name":"Resource consumption","score":0.45860040187835693},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44148746132850647},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.42140185832977295},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.40614157915115356},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.34214016795158386},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.2695837616920471},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.20947867631912231},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.14046066999435425}],"concepts":[{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.8558000326156616},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8038155436515808},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.646848738193512},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.5865781307220459},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5668815970420837},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.5469874739646912},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5361143946647644},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5242781043052673},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4637959599494934},{"id":"https://openalex.org/C2777480716","wikidata":"https://www.wikidata.org/wiki/Q23582796","display_name":"Resource consumption","level":2,"score":0.45860040187835693},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44148746132850647},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.42140185832977295},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40614157915115356},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.34214016795158386},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2695837616920471},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.20947867631912231},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.14046066999435425},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3580305.3599415","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3580305.3599415","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/4c3623ee-5cfd-4234-9522-e790a76444cb","is_oa":false,"landing_page_url":"https://vbn.aau.dk/da/publications/4c3623ee-5cfd-4234-9522-e790a76444cb","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Yang, S B, Hu, J, Guo, C, Yang, B & Jensen, C S 2023, LightPath : Lightweight and Scalable Path Representation Learning. in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. Association for Computing Machinery (ACM), Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 2999-3010, 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, Long Beach, United States, 06/08/2023. https://doi.org/10.1145/3580305.3599415","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8","score":0.5799999833106995}],"awards":[{"id":"https://openalex.org/G6688918602","display_name":null,"funder_award_id":"34328","funder_id":"https://openalex.org/F4320310490","funder_display_name":"Villum Fonden"}],"funders":[{"id":"https://openalex.org/F4320310490","display_name":"Villum Fonden","ror":"https://ror.org/007ww2d15"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2910892140","https://openalex.org/W2952493731","https://openalex.org/W2962756421","https://openalex.org/W2982321152","https://openalex.org/W3005661826","https://openalex.org/W3030299187","https://openalex.org/W3080548826","https://openalex.org/W3082160640","https://openalex.org/W3084879683","https://openalex.org/W3087903024","https://openalex.org/W3116489684","https://openalex.org/W3127035078","https://openalex.org/W3150739942","https://openalex.org/W3164820482","https://openalex.org/W3170874841","https://openalex.org/W3173213819","https://openalex.org/W3187633063","https://openalex.org/W3210395416","https://openalex.org/W4225862894","https://openalex.org/W4289533938","https://openalex.org/W4290876361","https://openalex.org/W4291127070","https://openalex.org/W6601412066","https://openalex.org/W6839796232"],"related_works":["https://openalex.org/W2983142544","https://openalex.org/W2891059443","https://openalex.org/W4281663961","https://openalex.org/W3208888551","https://openalex.org/W4313561566","https://openalex.org/W3208386644","https://openalex.org/W4220682630","https://openalex.org/W4389832810","https://openalex.org/W3163146846","https://openalex.org/W3133533225"],"abstract_inverted_index":{"Movement":[0],"paths":[1,25],"are":[2],"used":[3,33],"widely":[4],"in":[5,61],"intelligent":[6],"transportation":[7],"and":[8,29,42,59,64,81,90,96,110,169,193],"smart":[9],"city":[10],"applications.":[11],"To":[12],"serve":[13],"such":[14,38],"applications,":[15],"path":[16,40,54,74,98,139,156,175],"representation":[17,55,75,99],"learning":[18,56,76,100],"aims":[19,105],"to":[20,87,106,138,148,164,186],"provide":[21],"compact":[22],"representations":[23],"of":[24,152,173,195],"that":[26,52,104,128,130],"enable":[27,149],"efficient":[28],"accurate":[30],"operations":[31],"when":[32],"for":[34],"different":[35],"downstream":[36],"tasks":[37],"as":[39],"ranking":[41],"travel":[43],"cost":[44],"estimation.":[45],"In":[46],"many":[47],"cases,":[48],"it":[49,69],"is":[50,57,70],"attractive":[51],"the":[53,131,167,171,190,196],"lightweight":[58,95],"scalable;":[60],"resource-limited":[62],"environments":[63],"under":[65],"green":[66],"computing":[67],"limitations,":[68],"essential.":[71],"Yet,":[72],"existing":[73],"studies":[77],"focus":[78],"on":[79,182],"accuracy":[80],"pay":[82],"at":[83],"most":[84],"secondary":[85],"attention":[86],"resource":[88,108],"consumption":[89,109],"scalability.":[91],"We":[92,158],"propose":[93,124,143,160],"a":[94,125,144],"scalable":[97],"framework,":[101],"termed":[102],"LightPath,":[103],"reduce":[107,166],"achieve":[111],"scalability":[112,135],"without":[113],"affecting":[114],"accuracy,":[115],"thus":[116],"enabling":[117],"broader":[118],"applicability.":[119],"More":[120],"specifically,":[121],"we":[122,142,178],"first":[123],"sparse":[126,155,174],"auto-encoder":[127],"ensures":[129],"framework":[132,147],"achieves":[133],"good":[134],"with":[136],"respect":[137],"length.":[140],"Next,":[141],"relational":[145],"reasoning":[146],"faster":[150],"training":[151],"more":[153],"robust":[154],"encoders.":[157,176],"also":[159],"global-local":[161],"knowledge":[162],"distillation":[163],"further":[165],"size":[168],"improve":[170],"performance":[172],"Finally,":[177],"report":[179],"extensive":[180],"experiments":[181],"two":[183],"real-world":[184],"datasets":[185],"offer":[187],"insight":[188],"into":[189],"efficiency,":[191],"scalability,":[192],"effectiveness":[194],"proposed":[197],"framework.":[198]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}