{"id":"https://openalex.org/W4400909759","doi":"https://doi.org/10.1109/icde60146.2024.00033","title":"Efficient Example-Guided Interactive Graph Search","display_name":"Efficient Example-Guided Interactive Graph Search","publication_year":2024,"publication_date":"2024-05-13","ids":{"openalex":"https://openalex.org/W4400909759","doi":"https://doi.org/10.1109/icde60146.2024.00033"},"language":"en","primary_location":{"id":"doi:10.1109/icde60146.2024.00033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde60146.2024.00033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 40th International Conference on Data Engineering (ICDE)","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/A5042518350","display_name":"Zhuowei Zhao","orcid":"https://orcid.org/0000-0002-6891-6432"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zhuowei Zhao","raw_affiliation_strings":["University of Melbourne"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Melbourne","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068471095","display_name":"Junhao Gan","orcid":"https://orcid.org/0000-0001-9101-1503"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Junhao Gan","raw_affiliation_strings":["University of Melbourne"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Melbourne","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022290876","display_name":"Jianzhong Qi","orcid":"https://orcid.org/0000-0001-6501-9050"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jianzhong Qi","raw_affiliation_strings":["University of Melbourne"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Melbourne","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080660416","display_name":"Zhifeng Bao","orcid":"https://orcid.org/0000-0003-2477-381X"},"institutions":[{"id":"https://openalex.org/I4210095297","display_name":"MIT University","ror":"https://ror.org/00v140q16","country_code":"MK","type":"education","lineage":["https://openalex.org/I4210095297"]},{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU","MK"],"is_corresponding":false,"raw_author_name":"Zhifeng Bao","raw_affiliation_strings":["RMIT University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"RMIT University","institution_ids":["https://openalex.org/I4210095297","https://openalex.org/I82951845"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3057,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50325931,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"342","last_page":"354"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11106","display_name":"Data Management and Algorithms","score":0.9979000091552734,"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":0.9979000091552734,"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/T11574","display_name":"Artificial Intelligence in Games","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10317","display_name":"Advanced Database Systems and Queries","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.754430890083313},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4887518882751465},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4190068244934082}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.754430890083313},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4887518882751465},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4190068244934082}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icde60146.2024.00033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icde60146.2024.00033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 40th International Conference on Data Engineering (ICDE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1975489634","https://openalex.org/W2056748234","https://openalex.org/W2081118310","https://openalex.org/W2081580037","https://openalex.org/W2101620066","https://openalex.org/W2106675345","https://openalex.org/W2108598243","https://openalex.org/W2130055503","https://openalex.org/W2138965424","https://openalex.org/W2164124780","https://openalex.org/W2278629362","https://openalex.org/W2948179762","https://openalex.org/W3022673800","https://openalex.org/W3148000254","https://openalex.org/W4232632925","https://openalex.org/W4237139895","https://openalex.org/W4289533880","https://openalex.org/W4290943451","https://openalex.org/W4297971002","https://openalex.org/W6606988585","https://openalex.org/W6622957738","https://openalex.org/W6681400661","https://openalex.org/W6770734874"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"We":[0,190],"study":[1],"the":[2,16,21,52,68,86,93,108,131,134,137,144,156,174,228,252,272],"problem":[3],"of":[4,54,79,88,119,133,139,176,202,236,240,255],"interactive":[5],"graph":[6,28],"search":[7],"(IGS).":[8],"Given":[9],"a":[10,25,49,115,195,261],"query":[11,101,116,197,241],"entity":[12],"<tex":[13,32,38,56,62,120,127,140,148,187],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[14,33,39,57,63,121,128,141,149,188],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\varphi$</tex>,":[15,40],"goal":[17],"is":[18,65,83,97,130,205,244],"to":[19,60,91,99,143,186,233],"identify":[20,92],"target":[22,94,145],"concept":[23,30,61],"in":[24,51,208,238,246],"directed":[26],"acyclic":[27],"(DAG)":[29],"hierarchy":[31],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$H$</tex>,":[34],"which":[35,96],"best":[36],"describes":[37],"through":[41],"interactions":[42],"with":[43,268],"an":[44,80,166],"oracle.":[45,273],"In":[46,103,161],"each":[47],"interaction,":[48],"question":[50],"form":[53],"\u201cDoes":[55],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\varphi$</tex>":[58],"belong":[59],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$u?$</tex>\u201d":[64],"asked":[66],"and":[67,178,204,219,243],"oracle":[69],"can":[70],"only":[71],"answer":[72],"either":[73],"YES":[74],"or":[75],"NO.":[76],"The":[77],"efficiency":[78],"IGS":[81,110,170],"algorithm":[82,112,167],"measured":[84],"by":[85,183,231],"number":[87],"questions":[89,181],"asked,":[90],"concept,":[95],"referred":[98],"as":[100,271],"cost.":[102],"theory":[104],"aspect,":[105,163],"we":[106,164,259],"propose":[107,165],"Target-Sensitive":[109],"(TS-IGS)":[111],"that":[113,172,192,201,223],"achieves":[114,194],"cost":[117,198],"complexity":[118],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$O(\\log":[122],"n.":[123],"\\log\\frac{L}{\\log":[124],"n}+d\\cdot\\log_{d}n)$</tex>,":[125],"where":[126],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$L$</tex>":[129],"length":[132],"path":[135],"from":[136],"root":[138],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$H$</tex>":[142],"concept.":[146],"When":[147],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$L\\in":[150],"O(\\log":[151],"n)$</tex>,":[152],"our":[153,224,256],"TS-IGS":[154],"matches":[155],"known":[157],"lower":[158],"bound":[159,199],"[1].":[160],"practice":[162],"called":[168],"Example-Guided":[169],"(EG-IGS)":[171],"exploits":[173],"knowledge":[175],"entities":[177],"asks":[179],"promising":[180],"guided":[182],"examples":[184],"similar":[185],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\varphi$</tex>.":[189],"prove":[191],"EG-IGS":[193,225,257],"finer-grained":[196],"than":[200],"TS-IGS,":[203],"extremely":[206],"efficient":[207],"practice.":[209],"Extensive":[210],"experiments":[211],"on":[212],"six":[213],"real-world":[214],"datasets":[215],"(including":[216],"images,":[217],"texts,":[218],"gene":[220],"sequences)":[221],"show":[222],"outperforms":[226],"all":[227],"existing":[229],"competitors":[230],"up":[232],"two":[234],"orders":[235],"magnitude":[237],"terms":[239],"cost,":[242],"robust":[245],"various":[247],"settings.":[248],"To":[249],"further":[250],"demonstrate":[251],"real":[253],"feasibility":[254],"technique,":[258],"develop":[260],"fully-automatic":[262],"Amazon":[263],"product":[264],"categorization":[265],"demo":[266],"system":[267],"GPT-3.5":[269],"serving":[270]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
