{"id":"https://openalex.org/W2539377436","doi":"https://doi.org/10.1109/tkde.2016.2621038","title":"Influence Maximization in Trajectory Databases","display_name":"Influence Maximization in Trajectory Databases","publication_year":2016,"publication_date":"2016-10-25","ids":{"openalex":"https://openalex.org/W2539377436","doi":"https://doi.org/10.1109/tkde.2016.2621038","mag":"2539377436"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2016.2621038","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2016.2621038","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5101745644","display_name":"Long Guo","orcid":"https://orcid.org/0009-0004-9796-2237"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Long Guo","raw_affiliation_strings":["Key Lab of High Confidence Software Technologies (MOE), School of EECS, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Lab of High Confidence Software Technologies (MOE), School of EECS, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011200911","display_name":"Dongxiang Zhang","orcid":"https://orcid.org/0000-0002-9964-2470"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongxiang Zhang","raw_affiliation_strings":["School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045198704","display_name":"Gao Cong","orcid":"https://orcid.org/0000-0002-4430-6373"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Gao Cong","raw_affiliation_strings":["School of Computer Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computer Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101726779","display_name":"Wei Wu","orcid":"https://orcid.org/0000-0003-1781-5129"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Wu","raw_affiliation_strings":["Visa Inc, Singapore"],"affiliations":[{"raw_affiliation_string":"Visa Inc, Singapore","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077593594","display_name":"Kian\u2010Lee Tan","orcid":"https://orcid.org/0000-0001-9315-4057"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Kian-Lee Tan","raw_affiliation_strings":["School of Computing, National University of Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computing, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101745644"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":6.3045,"has_fulltext":false,"cited_by_count":57,"citation_normalized_percentile":{"value":0.97266881,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"29","issue":"3","first_page":"627","last_page":"641"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.993399977684021,"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/T10757","display_name":"Geographic Information Systems Studies","score":0.9757999777793884,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7958778738975525},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7945843935012817},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.7017146348953247},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5997759103775024},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.5796994566917419},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.5743833780288696},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.505645751953125},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4408611059188843},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.41906440258026123},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.3672468066215515},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35222941637039185},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2079433798789978},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15588340163230896}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7958778738975525},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7945843935012817},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.7017146348953247},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5997759103775024},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.5796994566917419},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.5743833780288696},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.505645751953125},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4408611059188843},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.41906440258026123},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.3672468066215515},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35222941637039185},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2079433798789978},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15588340163230896},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2016.2621038","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2016.2621038","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2592842074","display_name":null,"funder_award_id":"61602087","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320320671","display_name":"National Research Foundation","ror":"https://ror.org/05s0g1g46"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W59445306","https://openalex.org/W137627111","https://openalex.org/W1513288538","https://openalex.org/W1944367023","https://openalex.org/W1978073991","https://openalex.org/W1984069252","https://openalex.org/W1991635064","https://openalex.org/W2024626449","https://openalex.org/W2042123098","https://openalex.org/W2053105309","https://openalex.org/W2056473436","https://openalex.org/W2056609785","https://openalex.org/W2061820396","https://openalex.org/W2077738931","https://openalex.org/W2084077236","https://openalex.org/W2102086994","https://openalex.org/W2108278206","https://openalex.org/W2108858998","https://openalex.org/W2132801025","https://openalex.org/W2141403143","https://openalex.org/W2185001246","https://openalex.org/W2398182780","https://openalex.org/W2398784425","https://openalex.org/W2402355993","https://openalex.org/W6602390995","https://openalex.org/W6605539553","https://openalex.org/W6640862447","https://openalex.org/W6686670784","https://openalex.org/W6712241470","https://openalex.org/W7074596939"],"related_works":["https://openalex.org/W2891776881","https://openalex.org/W2101105382","https://openalex.org/W2244559970","https://openalex.org/W189876032","https://openalex.org/W2557467218","https://openalex.org/W2547236913","https://openalex.org/W2536297025","https://openalex.org/W2771290394","https://openalex.org/W2986650738","https://openalex.org/W4225293784"],"abstract_inverted_index":{"In":[0,66,96,154,171],"this":[1],"paper,":[2],"we":[3,70,98,114,156,174],"study":[4],"a":[5,31,40,80,100,116,133,141,167],"novel":[6,101],"problem":[7,49,159],"of":[8,43,64,87,123,169,193],"influence":[9,38,107],"maximization":[10],"in":[11,18,79],"trajectory":[12,77,102,185],"databases":[13],"that":[14,47,75,144],"is":[15,50,129],"very":[16],"useful":[17],"precise":[19],"location-aware":[20],"advertising.":[21],"It":[22],"finds":[23],"k":[24],"best":[25,62],"trajectories":[26],"to":[27,59,92,104,160,178],"be":[28],"attached":[29],"with":[30,119],"given":[32],"advertisement":[33],"and":[34,52,56,83,184],"maximizes":[35],"the":[36,48,61,67,106,162,191],"expected":[37],"among":[39],"large":[41,112],"group":[42,168],"audience.":[44],"We":[45,138],"show":[46],"NP-hard":[51],"propose":[53,84,99,115,140],"both":[54],"exact":[55,68],"approximate":[57],"solutions":[58],"find":[60],"set":[63],"trajectories.":[65],"solution,":[69],"devise":[71],"an":[72,120],"expansion-based":[73],"framework":[74],"enumerates":[76],"combinations":[78],"best-first":[81],"manner":[82],"three":[85],"types":[86],"upper":[88],"bound":[89],"estimation":[90],"techniques":[91],"facilitate":[93],"early":[94],"termination.":[95],"addition,":[97,155],"index":[103],"reduce":[105],"calculation":[108],"cost.":[109],"To":[110],"support":[111,146,161],"k,":[113],"greedy":[117],"solution":[118],"approximation":[121,148],"ratio":[122,149],"(1":[124],"-":[125],"1/e),":[126],"whose":[127],"performance":[128],"further":[130],"optimized":[131],"by":[132],"new":[134],"proposed":[135,195],"cluster-based":[136],"method.":[137],"also":[139],"threshold":[142],"method":[143],"can":[145],"any":[147],"\u03f5":[150],"\u2208":[151],"(0,":[152],"1].":[153],"extend":[157],"our":[158,172,194],"scenario":[163],"when":[164],"there":[165],"are":[166],"advertisements.":[170],"experiments,":[173],"use":[175],"real":[176],"datasets":[177],"construct":[179],"user":[180],"profiles,":[181],"motion":[182],"patterns,":[183],"databases.":[186],"The":[187],"experimental":[188],"results":[189],"verified":[190],"efficiency":[192],"methods.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
