{"id":"https://openalex.org/W2121804177","doi":"https://doi.org/10.1145/2666310.2666485","title":"Towards knowledge-enriched path computation","display_name":"Towards knowledge-enriched path computation","publication_year":2014,"publication_date":"2014-11-04","ids":{"openalex":"https://openalex.org/W2121804177","doi":"https://doi.org/10.1145/2666310.2666485","mag":"2121804177"},"language":"en","primary_location":{"id":"doi:10.1145/2666310.2666485","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2666310.2666485","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1409.2585","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Georgios Skoumas","orcid":null},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Georgios Skoumas","raw_affiliation_strings":["National Technical University of Athens, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Technical University of Athens, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Klaus Arthur Schmid","orcid":null},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Klaus Arthur Schmid","raw_affiliation_strings":["Ludwig-Maximilians-Universit\u00e1t M\u00fcnchen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ludwig-Maximilians-Universit\u00e1t M\u00fcnchen","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Gregor Joss\u00e9","orcid":null},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Gregor Joss\u00e9","raw_affiliation_strings":["Ludwig-Maximilians-Universit\u00e1t M\u00fcnchen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ludwig-Maximilians-Universit\u00e1t M\u00fcnchen","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Andreas Z\u00fcfle","orcid":null},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andreas Z\u00fcfle","raw_affiliation_strings":["Ludwig-Maximilians-Universit\u00e1t M\u00fcnchen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ludwig-Maximilians-Universit\u00e1t M\u00fcnchen","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Mario A. Nascimento","orcid":null},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mario A. Nascimento","raw_affiliation_strings":["University of Alberta, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Alberta, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Matthias Renz","orcid":null},"institutions":[{"id":"https://openalex.org/I8204097","display_name":"Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen","ror":"https://ror.org/05591te55","country_code":"DE","type":"education","lineage":["https://openalex.org/I8204097"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Matthias Renz","raw_affiliation_strings":["Ludwig-Maximilians-Universit\u00e1t M\u00fcnchen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ludwig-Maximilians-Universit\u00e1t M\u00fcnchen","institution_ids":["https://openalex.org/I8204097"]}]},{"author_position":"last","author":{"id":null,"display_name":"Dieter Pfoser","orcid":null},"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":"Dieter Pfoser","raw_affiliation_strings":["George Mason University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"George Mason University","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"485","last_page":"488"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9998000264167786,"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/T10757","display_name":"Geographic Information Systems Studies","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/3305","display_name":"Geography, Planning and Development"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9907000064849854,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/closeness","display_name":"Closeness","score":0.6807000041007996},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6197999715805054},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.6162999868392944},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5494999885559082},{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.5397999882698059},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5360000133514404},{"id":"https://openalex.org/keywords/routing","display_name":"Routing (electronic design automation)","score":0.459199994802475},{"id":"https://openalex.org/keywords/shortest-path-problem","display_name":"Shortest path problem","score":0.4372999966144562}],"concepts":[{"id":"https://openalex.org/C2779545769","wikidata":"https://www.wikidata.org/wiki/Q5135364","display_name":"Closeness","level":2,"score":0.6807000041007996},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6197999715805054},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.6162999868392944},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6032999753952026},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5494999885559082},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.5397999882698059},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5360000133514404},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5254999995231628},{"id":"https://openalex.org/C74172769","wikidata":"https://www.wikidata.org/wiki/Q1446839","display_name":"Routing (electronic design automation)","level":2,"score":0.459199994802475},{"id":"https://openalex.org/C22590252","wikidata":"https://www.wikidata.org/wiki/Q1058754","display_name":"Shortest path problem","level":3,"score":0.4372999966144562},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41819998621940613},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.41679999232292175},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.41339999437332153},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.40639999508857727},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3921000063419342},{"id":"https://openalex.org/C150140777","wikidata":"https://www.wikidata.org/wiki/Q960648","display_name":"Point of interest","level":2,"score":0.38019999861717224},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3276999890804291},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.3109999895095825},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3059000074863434},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.2994999885559082},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2935999929904938},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C129045301","wikidata":"https://www.wikidata.org/wiki/Q7144654","display_name":"Path length","level":2,"score":0.28519999980926514},{"id":"https://openalex.org/C27511587","wikidata":"https://www.wikidata.org/wiki/Q2178623","display_name":"Spatial relation","level":2,"score":0.2824000120162964},{"id":"https://openalex.org/C2639959","wikidata":"https://www.wikidata.org/wiki/Q1344778","display_name":"Distance measures","level":2,"score":0.2526000142097473}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/2666310.2666485","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2666310.2666485","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1409.2585","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1409.2585","pdf_url":"https://arxiv.org/pdf/1409.2585","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1409.2585","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1409.2585","pdf_url":"https://arxiv.org/pdf/1409.2585","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1491819754","https://openalex.org/W1510343741","https://openalex.org/W1972853209","https://openalex.org/W2039001267","https://openalex.org/W2061651455","https://openalex.org/W2121804177","https://openalex.org/W2143017621","https://openalex.org/W4299533127"],"related_works":[],"abstract_inverted_index":{"Directions":[0],"and":[1,79,181],"paths,":[2,177],"as":[3,60,143],"commonly":[4],"provided":[5],"by":[6,53],"navigation":[7],"systems,":[8],"are":[9],"usually":[10],"derived":[11],"considering":[12],"absolute":[13],"metrics,":[14],"e.g.,":[15],"finding":[16],"the":[17,26,102,108,130,161,185],"shortest":[18],"path":[19,170],"within":[20],"an":[21,114],"underlying":[22],"road":[23,110,132],"network.":[24],"With":[25],"aid":[27],"of":[28,74,76,82,97,169],"crowdsourced":[29,119],"geospatial":[30],"data":[31,142],"we":[32,92,112,138],"aim":[33],"at":[34],"obtaining":[35],"paths":[36,163],"that":[37,69,160],"do":[38],"not":[39],"only":[40],"minimize":[41],"distance":[42],"but":[43],"also":[44,173],"lead":[45],"through":[46],"more":[47,175,182],"popular":[48],"areas":[49],"using":[50,85],"knowledge":[51],"generated":[52],"users.":[54],"We":[55,124],"extract":[56],"spatial":[57,98,120],"relations":[58,84,121],"such":[59],"\"nearby\"":[61],"or":[62],"\"next":[63],"to\"":[64],"from":[65],"geo-textual":[66],"travel":[67],"blogs,":[68],"define":[70],"closeness":[71,99],"between":[72],"pairs":[73],"points":[75],"interest":[77],"(POIs)":[78],"quantify":[80],"each":[81],"these":[83],"a":[86,94,144],"probabilistic":[87,95],"model.":[88],"Using":[89],"Bayesian":[90],"inference,":[91],"obtain":[93],"measure":[96,106],"according":[100],"to":[101,107],"crowd.":[103],"Applying":[104],"this":[105],"corresponding":[109],"network,":[111],"derive":[113],"altered":[115],"cost":[116],"function":[117],"taking":[118],"into":[122],"account.":[123],"propose":[125],"two":[126],"routing":[127,179],"algorithms":[128],"on":[129,154],"enriched":[131],"networks.":[133],"To":[134],"evaluate":[135],"our":[136],"approach,":[137],"use":[139],"Flickr":[140],"photo":[141],"ground":[145],"truth":[146],"for":[147,184],"popularity.":[148],"Our":[149],"experimental":[150],"results":[151],"--":[152,158],"based":[153],"real":[155],"world":[156],"datasets":[157],"show":[159],"computed":[162],"yield":[164],"competitive":[165],"solutions":[166],"in":[167],"terms":[168],"length":[171],"while":[172],"providing":[174],"\"popular\"":[176],"making":[178],"easier":[180],"informative":[183],"user.":[186]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2016-06-24T00:00:00"}