{"id":"https://openalex.org/W2965425016","doi":"https://doi.org/10.1145/3292500.3332298","title":"Modeling and Applications for Temporal Point Processes","display_name":"Modeling and Applications for Temporal Point Processes","publication_year":2019,"publication_date":"2019-07-25","ids":{"openalex":"https://openalex.org/W2965425016","doi":"https://doi.org/10.1145/3292500.3332298","mag":"2965425016"},"language":"en","primary_location":{"id":"doi:10.1145/3292500.3332298","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3332298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; 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/A5087158377","display_name":"Junchi Yan","orcid":"https://orcid.org/0000-0001-9639-7679"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Junchi Yan","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035141289","display_name":"Hongteng Xu","orcid":"https://orcid.org/0000-0003-4192-5360"},"institutions":[{"id":"https://openalex.org/I4210093512","display_name":"Infinia ML (United States)","ror":"https://ror.org/00gd30v42","country_code":"US","type":"company","lineage":["https://openalex.org/I4210093512"]},{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongteng Xu","raw_affiliation_strings":["Infinia ML, Inc. &amp; Duke University, Durham, NC, USA"],"affiliations":[{"raw_affiliation_string":"Infinia ML, Inc. &amp; Duke University, Durham, NC, USA","institution_ids":["https://openalex.org/I4210093512","https://openalex.org/I170897317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020114308","display_name":"Liangda Li","orcid":"https://orcid.org/0000-0002-2883-7529"},"institutions":[{"id":"https://openalex.org/I4210134091","display_name":"Yahoo (United States)","ror":"https://ror.org/040dkzz12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134091"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liangda Li","raw_affiliation_strings":["Yahoo! Research, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"Yahoo! Research, Sunnyvale, CA, USA","institution_ids":["https://openalex.org/I4210134091"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5087158377"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":4.3187,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.95141566,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3227","last_page":"3228"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11830","display_name":"Point processes and geometric inequalities","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11830","display_name":"Point processes and geometric inequalities","score":0.9955000281333923,"subfield":{"id":"https://openalex.org/subfields/2604","display_name":"Applied Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13187","display_name":"Diffusion and Search Dynamics","score":0.9050999879837036,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7819429636001587},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.7518287897109985},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6657400131225586},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.651603639125824},{"id":"https://openalex.org/keywords/point-process","display_name":"Point process","score":0.6081718802452087},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5855559706687927},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.5324517488479614},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.5142900347709656},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5039834380149841},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.43273282051086426},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.42519986629486084},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4146236181259155}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7819429636001587},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.7518287897109985},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6657400131225586},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.651603639125824},{"id":"https://openalex.org/C88871306","wikidata":"https://www.wikidata.org/wiki/Q7208287","display_name":"Point process","level":2,"score":0.6081718802452087},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5855559706687927},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.5324517488479614},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.5142900347709656},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5039834380149841},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.43273282051086426},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.42519986629486084},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4146236181259155},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3292500.3332298","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3292500.3332298","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.8100000023841858,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1594866779","https://openalex.org/W1972754097","https://openalex.org/W1972882261","https://openalex.org/W1999735946","https://openalex.org/W2043686656","https://openalex.org/W2064758233","https://openalex.org/W2071778976","https://openalex.org/W2087822214","https://openalex.org/W2102881014","https://openalex.org/W2127434196","https://openalex.org/W2187486022","https://openalex.org/W2252784747","https://openalex.org/W2287439151","https://openalex.org/W2401267531","https://openalex.org/W2571789045","https://openalex.org/W2574051726","https://openalex.org/W2585868976","https://openalex.org/W2604792366","https://openalex.org/W2605191235","https://openalex.org/W2617104629","https://openalex.org/W2787256428","https://openalex.org/W2788849864","https://openalex.org/W2807751666","https://openalex.org/W2914034186","https://openalex.org/W2950078347","https://openalex.org/W2951056918","https://openalex.org/W2962718388","https://openalex.org/W2963087811","https://openalex.org/W3007327886","https://openalex.org/W3104043521"],"related_works":["https://openalex.org/W4367722749","https://openalex.org/W4312200629","https://openalex.org/W4223943233","https://openalex.org/W4360585206","https://openalex.org/W4364306694","https://openalex.org/W3024390022","https://openalex.org/W3198184493","https://openalex.org/W2984518291","https://openalex.org/W4309045103","https://openalex.org/W3159117918"],"abstract_inverted_index":{"Real-world":[0],"entities'":[1],"behaviors,":[2],"associated":[3],"with":[4,91,133],"their":[5],"side":[6],"information,":[7],"are":[8,20],"often":[9],"recorded":[10],"over":[11],"time":[12],"as":[13],"asynchronous":[14,67],"event":[15,18,68,101,107],"sequences.":[16],"Such":[17],"sequences":[19],"the":[21,62,72,77,80,97],"basis":[22],"of":[23,66,76,100],"many":[24,122],"practical":[25],"applications,":[26],"neural":[27],"spiking":[28],"train":[29],"study,":[30],"earth":[31],"quack":[32],"prediction,":[33],"crime":[34],"analysis,":[35],"infectious":[36],"disease":[37],"diffusion":[38],"forecasting,":[39],"condition-based":[40],"preventative":[41],"maintenance,":[42],"information":[43],"retrieval":[44],"and":[45,49,64,79,85,109,125,129,146],"behavior-based":[46],"network":[47],"analysis":[48],"services,":[50],"etc.":[51],"Temporal":[52],"point":[53],"process":[54],"(TPP)":[55],"is":[56,104],"a":[57],"principled":[58],"mathematical":[59],"tool":[60],"for":[61,106],"modeling":[63],"learning":[65,124,137],"sequences,":[69,102],"which":[70,103],"captures":[71],"instantaneous":[73],"happening":[74],"rate":[75],"events":[78],"temporal":[81],"dependency":[82],"between":[83],"historical":[84],"current":[86],"events.":[87],"TPP":[88,118],"provides":[89],"us":[90],"an":[92],"interpretable":[93],"model":[94],"to":[95,121],"describe":[96],"generative":[98],"mechanism":[99],"beneficial":[105],"prediction":[108],"causality":[110],"analysis.":[111],"Recently,":[112],"it":[113],"has":[114,119],"been":[115],"shown":[116],"that":[117],"potentials":[120],"machine":[123,136],"data":[126],"science":[127],"applications":[128],"can":[130],"be":[131],"combined":[132],"other":[134],"cutting-edge":[135],"techniques":[138],"like":[139],"deep":[140],"learning,":[141,143,145],"reinforcement":[142],"adversarial":[144],"so":[147],"on.":[148]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3}],"updated_date":"2026-03-04T09:10:02.777135","created_date":"2025-10-10T00:00:00"}
