{"id":"https://openalex.org/W4384471465","doi":"https://doi.org/10.1007/978-3-031-37706-8_23","title":"Synthesizing Trajectory Queries from\u00a0Examples","display_name":"Synthesizing Trajectory Queries from\u00a0Examples","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4384471465","doi":"https://doi.org/10.1007/978-3-031-37706-8_23"},"language":"en","primary_location":{"id":"doi:10.1007/978-3-031-37706-8_23","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-37706-8_23","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-031-37706-8_23.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/978-3-031-37706-8_23.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022106651","display_name":"Stephen Mell","orcid":"https://orcid.org/0009-0003-7469-8974"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Stephen Mell","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, PA, 19104, USA"],"affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, PA, 19104, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060297001","display_name":"Favyen Bastani","orcid":"https://orcid.org/0000-0002-1100-4192"},"institutions":[{"id":"https://openalex.org/I4210140341","display_name":"Allen Institute","ror":"https://ror.org/03cpe7c52","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210140341"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Favyen Bastani","raw_affiliation_strings":["Allen Institute for AI, Seattle, WA, 98104, USA"],"affiliations":[{"raw_affiliation_string":"Allen Institute for AI, Seattle, WA, 98104, USA","institution_ids":["https://openalex.org/I4210140341"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041830534","display_name":"Steve Zdancewic","orcid":"https://orcid.org/0000-0002-3516-1512"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Steve Zdancewic","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, PA, 19104, USA"],"affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, PA, 19104, USA","institution_ids":["https://openalex.org/I79576946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029243071","display_name":"Osbert Bastani","orcid":"https://orcid.org/0000-0001-9990-7566"},"institutions":[{"id":"https://openalex.org/I79576946","display_name":"University of Pennsylvania","ror":"https://ror.org/00b30xv10","country_code":"US","type":"education","lineage":["https://openalex.org/I79576946"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Osbert Bastani","raw_affiliation_strings":["University of Pennsylvania, Philadelphia, PA, 19104, USA"],"affiliations":[{"raw_affiliation_string":"University of Pennsylvania, Philadelphia, PA, 19104, USA","institution_ids":["https://openalex.org/I79576946"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5022106651"],"corresponding_institution_ids":["https://openalex.org/I79576946"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":{"value":5000,"currency":"EUR","value_usd":5392},"fwci":1.9886,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.9126485,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"459","last_page":"484"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.996399998664856,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9156613945960999},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.7005661725997925},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6627757549285889},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6147254109382629},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6027112007141113},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5553542375564575},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5548928380012512},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.484140008687973},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4564010202884674},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.45131707191467285},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4190725088119507},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.39292383193969727},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38001787662506104},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.373668909072876},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.17523488402366638}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9156613945960999},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.7005661725997925},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6627757549285889},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6147254109382629},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6027112007141113},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5553542375564575},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5548928380012512},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.484140008687973},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4564010202884674},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.45131707191467285},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4190725088119507},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.39292383193969727},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38001787662506104},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.373668909072876},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.17523488402366638},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C6557445","wikidata":"https://www.wikidata.org/wiki/Q173113","display_name":"Agronomy","level":1,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","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},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/978-3-031-37706-8_23","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-37706-8_23","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-031-37706-8_23.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},{"id":"pmh:oai:arXiv.org:2602.15164","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2602.15164","pdf_url":"https://arxiv.org/pdf/2602.15164","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1007/978-3-031-37706-8_23","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-3-031-37706-8_23","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-3-031-37706-8_23.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6299999952316284}],"awards":[{"id":"https://openalex.org/G3231474415","display_name":"Expeditions: Collaborative Research: Understanding the World Through Code","funder_award_id":"1917852","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G5245263354","display_name":null,"funder_award_id":"CCF-1910769","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6074853558","display_name":null,"funder_award_id":"W911NF-20-1-0080","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G6901837805","display_name":"SHF: Small: Inferring Specifications for Blackbox Code","funder_award_id":"1910769","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7452299184","display_name":null,"funder_award_id":"W911NF","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G8998121839","display_name":null,"funder_award_id":"911NF","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4384471465.pdf"},"referenced_works_count":60,"referenced_works":["https://openalex.org/W828139470","https://openalex.org/W1547304883","https://openalex.org/W1998368317","https://openalex.org/W2005865076","https://openalex.org/W2026775511","https://openalex.org/W2049399166","https://openalex.org/W2064675550","https://openalex.org/W2086092403","https://openalex.org/W2094878426","https://openalex.org/W2166779535","https://openalex.org/W2169998728","https://openalex.org/W2194775991","https://openalex.org/W2257979135","https://openalex.org/W2276356546","https://openalex.org/W2294286398","https://openalex.org/W2470394683","https://openalex.org/W2474788619","https://openalex.org/W2519586580","https://openalex.org/W2565370028","https://openalex.org/W2600080636","https://openalex.org/W2603203130","https://openalex.org/W2618530766","https://openalex.org/W2739464847","https://openalex.org/W2789410150","https://openalex.org/W2884958048","https://openalex.org/W2911273949","https://openalex.org/W2912432686","https://openalex.org/W2920942303","https://openalex.org/W2952402617","https://openalex.org/W2955189650","https://openalex.org/W2956034981","https://openalex.org/W2963427179","https://openalex.org/W2964147651","https://openalex.org/W2965522163","https://openalex.org/W2980133010","https://openalex.org/W2981393651","https://openalex.org/W2982349156","https://openalex.org/W3000318171","https://openalex.org/W3017682360","https://openalex.org/W3021068062","https://openalex.org/W3028942915","https://openalex.org/W3033481405","https://openalex.org/W3086715908","https://openalex.org/W3092068599","https://openalex.org/W3098394944","https://openalex.org/W3106772683","https://openalex.org/W3118240751","https://openalex.org/W3136017576","https://openalex.org/W3140654866","https://openalex.org/W3171035942","https://openalex.org/W3203641084","https://openalex.org/W4235951092","https://openalex.org/W4243061752","https://openalex.org/W4251429682","https://openalex.org/W4299968636","https://openalex.org/W4318976340","https://openalex.org/W4384471465","https://openalex.org/W6633872374","https://openalex.org/W6739901393","https://openalex.org/W6926331673"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W4230315250","https://openalex.org/W2086519370","https://openalex.org/W2087343574"],"abstract_inverted_index":{"Abstract":[0],"Data":[1],"scientists":[2],"often":[3,42],"need":[4],"to":[5,8,32],"write":[6],"programs":[7],"process":[9],"predictions":[10],"of":[11,36,67,99],"machine":[12],"learning":[13],"models,":[14],"such":[15,26],"as":[16],"object":[17],"detections":[18],"and":[19,83,107,119],"trajectories":[20],"in":[21,39],"video":[22],"data.":[23],"However,":[24],"writing":[25],"queries":[27,62,115],"can":[28,112],"be":[29,48],"challenging":[30],"due":[31],"the":[33,80],"fuzzy":[34],"nature":[35],"real-world":[37],"data;":[38],"particular,":[40],"they":[41],"include":[43],"real-valued":[44],"parameters":[45],"that":[46,59,88,110,120],"must":[47],"tuned":[49],"by":[50],"hand.":[51],"We":[52,93],"propose":[53],"a":[54,64,75,84,97],"novel":[55,76,85],"framework":[56],"called":[57],"Quivr":[58,95],"synthesizes":[60],"trajectory":[61],"matching":[63],"given":[65],"set":[66],"examples.":[68],"To":[69],"efficiently":[70],"synthesize":[71,113],"parameters,":[72],"we":[73],"introduce":[74],"technique":[77],"for":[78,116],"pruning":[79],"parameter":[81],"space":[82],"quantitative":[86],"semantics":[87],"makes":[89],"this":[90],"more":[91],"efficient.":[92],"evaluate":[94],"on":[96],"benchmark":[98],"17":[100],"tasks,":[101],"including":[102],"several":[103],"from":[104],"prior":[105],"work,":[106],"show":[108],"both":[109],"it":[111],"accurate":[114],"each":[117],"task":[118],"our":[121],"optimizations":[122],"substantially":[123],"reduce":[124],"synthesis":[125],"time.":[126]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}