{"id":"https://openalex.org/W6925569803","doi":"https://doi.org/10.18420/inf2022_20","title":"D-TOUR: Detour-based point of interest detection in privacy-sensitive trajectories","display_name":"D-TOUR: Detour-based point of interest detection in privacy-sensitive trajectories","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W6925569803","doi":"https://doi.org/10.18420/inf2022_20"},"language":"en","primary_location":{"id":"doi:10.18420/inf2022_20","is_oa":true,"landing_page_url":"https://doi.org/10.18420/inf2022_20","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.18420/inf2022_20","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Schneider, Maja","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Schneider, Maja","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Gehrke, Lukas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gehrke, Lukas","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Christen, Peter","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Christen, Peter","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":null,"display_name":"Rahm, Erhard","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rahm, Erhard","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.21805008,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T11073","display_name":"Metal Extraction and Bioleaching","score":0.9369000196456909,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/T11073","display_name":"Metal Extraction and Bioleaching","score":0.9369000196456909,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/T12458","display_name":"Organometallic Compounds Synthesis and Characterization","score":0.012600000016391277,"subfield":{"id":"https://openalex.org/subfields/1605","display_name":"Organic Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10710","display_name":"Arsenic contamination and mitigation","score":0.002199999988079071,"subfield":{"id":"https://openalex.org/subfields/2304","display_name":"Environmental Chemistry"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.7770000100135803},{"id":"https://openalex.org/keywords/point-of-interest","display_name":"Point of interest","score":0.6531999707221985},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5177000164985657},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4885999858379364},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4684000015258789},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4422000050544739},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.38350000977516174}],"concepts":[{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.7770000100135803},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7161999940872192},{"id":"https://openalex.org/C150140777","wikidata":"https://www.wikidata.org/wiki/Q960648","display_name":"Point of interest","level":2,"score":0.6531999707221985},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5752000212669373},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5177000164985657},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4885999858379364},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4684000015258789},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4422000050544739},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.38350000977516174},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.3734000027179718},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.3659000098705292},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35420000553131104},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.329800009727478},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.30379998683929443},{"id":"https://openalex.org/C2777317252","wikidata":"https://www.wikidata.org/wiki/Q18393516","display_name":"Rare events","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.26739999651908875},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2635999917984009}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18420/inf2022_20","is_oa":true,"landing_page_url":"https://doi.org/10.18420/inf2022_20","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.18420/inf2022_20","is_oa":true,"landing_page_url":"https://doi.org/10.18420/inf2022_20","pdf_url":null,"source":{"id":"https://openalex.org/S7407052918","display_name":"Gesellschaft f\u00fcr Informatik (GI)","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"sustainable_development_goals":[{"score":0.8336774706840515,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Data":[0],"collected":[1],"through":[2],"mobile":[3],"sensors":[4],"on":[5,92,135,151],"private":[6,60],"and":[7,17,56,113,164],"commercial":[8],"devices":[9],"can":[10,33,45,99],"give":[11],"valuable":[12],"insights":[13],"into":[14],"mobility":[15],"patterns":[16],"facilitate":[18],"applications":[19],"such":[20,31,62],"as":[21,63],"urban":[22],"planning":[23],"or":[24,65],"traffic":[25],"forecasting.":[26],"At":[27],"the":[28,39,120,138,156],"same":[29],"time,":[30],"data":[32,40,87,95,153],"carry":[34],"immense":[35],"privacy":[36],"risks":[37],"for":[38,75],"producers.":[41],"Stop":[42],"detection":[43,123],"approaches":[44,80],"reveal":[46],"a":[47,106,111,127],"person's":[48],"points":[49],"of":[50,119],"interest":[51],"(POI)":[52],"by":[53,117],"clustering":[54],"temporal":[55],"spatial":[57],"features,":[58],"uncovering":[59],"attributes":[61],"home":[64],"work":[66],"addresses.":[67],"Privacy-preserving":[68],"mechanisms":[69],"aim":[70],"at":[71],"hiding":[72],"these":[73],"POIs,":[74],"example":[76],"via":[77],"speed":[78],"smoothing":[79,110],"that":[81,97,102,131,144],"are":[82,103,114],"able":[83],"to":[84,105],"preserve":[85],"high":[86],"utility.":[88],"We":[89,125],"show":[90],"experimentally":[91],"two":[93],"real-world":[94],"sets":[96],"trajectories":[98],"contain":[100],"anomalies":[101],"contained":[104],"certain":[107],"extent":[108],"when":[109,160],"route":[112,165],"not":[115],"detected":[116],"state":[118],"art":[121],"stop":[122],"algorithms.":[124],"propose":[126],"novel":[128],"attack":[129,147],"D-TOUR":[130],"reveals":[132],"POIs":[133],"based":[134],"deviations":[136],"from":[137],"optimal":[139],"route.":[140],"Our":[141],"experiments":[142],"suggest":[143],"our":[145],"proposed":[146],"has":[148],"similar":[149],"performance":[150],"unprotected":[152],"but":[154],"outperforms":[155],"baseline":[157],"approach,":[158],"especially":[159],"protection":[161],"is":[162],"higher":[163],"features":[166],"become":[167],"more":[168],"sparse.":[169]},"counts_by_year":[],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}
