{"id":"https://openalex.org/W2583504941","doi":"https://doi.org/10.1145/3018661.3018711","title":"Probabilistic Social Sequential Model for Tour Recommendation","display_name":"Probabilistic Social Sequential Model for Tour Recommendation","publication_year":2017,"publication_date":"2017-02-02","ids":{"openalex":"https://openalex.org/W2583504941","doi":"https://doi.org/10.1145/3018661.3018711","mag":"2583504941"},"language":"en","primary_location":{"id":"doi:10.1145/3018661.3018711","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3018661.3018711","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=3018711&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"http://dl.acm.org/ft_gateway.cfm?id=3018711&type=pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000202397","display_name":"Vineeth Rakesh","orcid":"https://orcid.org/0000-0001-7586-0257"},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Vineeth Rakesh","raw_affiliation_strings":["Wayne State University, Detroit, MI, USA"],"affiliations":[{"raw_affiliation_string":"Wayne State University, Detroit, MI, USA","institution_ids":["https://openalex.org/I185443292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037197363","display_name":"Niranjan Jadhav","orcid":null},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Niranjan Jadhav","raw_affiliation_strings":["Wayne State University, Detroit, MI, USA"],"affiliations":[{"raw_affiliation_string":"Wayne State University, Detroit, MI, USA","institution_ids":["https://openalex.org/I185443292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025168533","display_name":"Alexander Kotov","orcid":"https://orcid.org/0000-0002-9872-6605"},"institutions":[{"id":"https://openalex.org/I185443292","display_name":"Wayne State University","ror":"https://ror.org/01070mq45","country_code":"US","type":"education","lineage":["https://openalex.org/I185443292"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander Kotov","raw_affiliation_strings":["Wayne State University, Detroit, MI, USA"],"affiliations":[{"raw_affiliation_string":"Wayne State University, Detroit, MI, USA","institution_ids":["https://openalex.org/I185443292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001022750","display_name":"Chandan K. Reddy","orcid":"https://orcid.org/0000-0003-2839-3662"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chandan K. Reddy","raw_affiliation_strings":["Virginia Tech, Arlington, VA, USA"],"affiliations":[{"raw_affiliation_string":"Virginia Tech, Arlington, VA, USA","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5000202397"],"corresponding_institution_ids":["https://openalex.org/I185443292"],"apc_list":null,"apc_paid":null,"fwci":10.2773,"has_fulltext":true,"cited_by_count":28,"citation_normalized_percentile":{"value":0.97452414,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"631","last_page":"640"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9993000030517578,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11106","display_name":"Data Management and Algorithms","score":0.9959999918937683,"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/computer-science","display_name":"Computer science","score":0.8210289478302002},{"id":"https://openalex.org/keywords/point-of-interest","display_name":"Point of interest","score":0.6518532037734985},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6362652778625488},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.6140254139900208},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.5220522880554199},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5135688781738281},{"id":"https://openalex.org/keywords/personalization","display_name":"Personalization","score":0.48080959916114807},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.3275846838951111},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3017776608467102}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8210289478302002},{"id":"https://openalex.org/C150140777","wikidata":"https://www.wikidata.org/wiki/Q960648","display_name":"Point of interest","level":2,"score":0.6518532037734985},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6362652778625488},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.6140254139900208},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.5220522880554199},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5135688781738281},{"id":"https://openalex.org/C183003079","wikidata":"https://www.wikidata.org/wiki/Q1000371","display_name":"Personalization","level":2,"score":0.48080959916114807},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3275846838951111},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3017776608467102},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3018661.3018711","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3018661.3018711","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=3018711&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3018661.3018711","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3018661.3018711","pdf_url":"http://dl.acm.org/ft_gateway.cfm?id=3018711&type=pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G2037717774","display_name":"III: Small: Collaborative Research: Global Event and Trend Archive Research (GETAR)","funder_award_id":"1619028","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2690932125","display_name":null,"funder_award_id":"IIS-1707498","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3223590597","display_name":null,"funder_award_id":"IIS-1619028","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3343279563","display_name":"III: Small: New Machine Learning Approaches for Modeling Time-to-Event Data","funder_award_id":"1707498","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5743301901","display_name":null,"funder_award_id":"IIS-1646881","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6530261880","display_name":null,"funder_award_id":"IIS-1707498, IIS-1619028, IIS- 1646881","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2583504941.pdf","grobid_xml":"https://content.openalex.org/works/W2583504941.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W29350917","https://openalex.org/W177101540","https://openalex.org/W1546409232","https://openalex.org/W1880262756","https://openalex.org/W1965327747","https://openalex.org/W1969486090","https://openalex.org/W1984189333","https://openalex.org/W2003684386","https://openalex.org/W2015765807","https://openalex.org/W2017921654","https://openalex.org/W2019612011","https://openalex.org/W2045563097","https://openalex.org/W2054638116","https://openalex.org/W2059512502","https://openalex.org/W2067131913","https://openalex.org/W2072609015","https://openalex.org/W2072787293","https://openalex.org/W2073021764","https://openalex.org/W2076623641","https://openalex.org/W2081721999","https://openalex.org/W2082260230","https://openalex.org/W2087692915","https://openalex.org/W2097129520","https://openalex.org/W2104210067","https://openalex.org/W2121985689","https://openalex.org/W2127860643","https://openalex.org/W2140251882","https://openalex.org/W2149814409","https://openalex.org/W2161656991","https://openalex.org/W2223926708","https://openalex.org/W2244475425","https://openalex.org/W2248044446","https://openalex.org/W2255303685","https://openalex.org/W2256429733","https://openalex.org/W2294749418","https://openalex.org/W2405496393","https://openalex.org/W2434565296","https://openalex.org/W2567312369","https://openalex.org/W3122513349","https://openalex.org/W4230692091","https://openalex.org/W4254373586","https://openalex.org/W6600237587","https://openalex.org/W6601266828","https://openalex.org/W6601559548"],"related_works":["https://openalex.org/W2368605798","https://openalex.org/W2518037665","https://openalex.org/W2348524959","https://openalex.org/W2368049389","https://openalex.org/W2384861574","https://openalex.org/W2952704802","https://openalex.org/W4294565801","https://openalex.org/W2142306706","https://openalex.org/W2477036161","https://openalex.org/W2912355043"],"abstract_inverted_index":{"The":[0],"pervasive":[1],"growth":[2],"of":[3,31,44,47,56,58,72,101,161,166,177,189],"location-based":[4],"services":[5],"such":[6,79],"as":[7,80],"Foursquare":[8],"and":[9,69,83,158,200],"Yelp":[10],"has":[11],"enabled":[12],"researchers":[13],"to":[14,61,87,108,142,163],"incorpo-":[15],"rate":[16],"better":[17],"personalization":[18],"into":[19],"recommendation":[20,134,195,202],"models":[21],"by":[22,28,197],"leveraging":[23],"the":[24,45,74,92,152,159,191],"geo-temporal":[25],"breadcrumbs":[26],"left":[27],"a":[29,67,132,138,174],"plethora":[30],"travelers.":[32,125,204],"In":[33],"this":[34,110,128],"paper,":[35],"we":[36,130,182],"explore":[37],"Travel":[38],"path":[39],"recommendation,":[40],"which":[41],"is":[42,187],"one":[43],"applications":[46],"intelligent":[48],"urban":[49],"navigation":[50],"that":[51,119,136,184],"aims":[52],"in":[53,111],"recommending":[54],"sequence":[55,165],"point":[57],"interest":[59],"(POIs)":[60],"tourists.":[62,169],"Currently,":[63],"travelers":[64],"rely":[65],"on":[66],"tedious":[68],"time-consuming":[70],"process":[71],"searching":[73],"web,":[75],"browsing":[76],"through":[77],"websites":[78],"Trip":[81],"Advisor,":[82],"reading":[84],"travel":[85,154,178],"blogs":[86],"compile":[88],"an":[89],"itinerary.":[90],"On":[91],"other":[93],"hand,":[94],"people":[95],"who":[96],"do":[97,109],"not":[98],"plan":[99],"ahead":[100],"their":[102,149],"trip":[103],"find":[104],"it":[105],"extremely":[106],"difficult":[107],"real-time":[112],"since":[113],"there":[114],"are":[115],"no":[116],"automated":[117],"systems":[118],"can":[120],"provide":[121],"personalized":[122],"itinerary":[123],"for":[124,168,203],"To":[126],"tackle":[127],"problem,":[129],"propose":[131],"tour":[133,194],"model":[135,186,196],"uses":[137],"probabilistic":[139,193],"generative":[140],"framework":[141],"incorporate":[143],"user's":[144],"categorical":[145],"preference,":[146],"influence":[147],"from":[148,180],"social":[150],"circle,":[151],"dynamic":[153],"transitions":[155],"(or":[156],"patterns)":[157],"popularity":[160],"venues":[162],"recommend":[164],"POIs":[167],"Through":[170],"comprehensive":[171],"experiments":[172],"over":[173],"rich":[175],"dataset":[176],"patterns":[179],"Foursquare,":[181],"show":[183],"our":[185],"capable":[188],"outperforming":[190],"state-of-the-art":[192],"providing":[198],"contextual":[199],"meaningful":[201]},"counts_by_year":[{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":10}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
