{"id":"https://openalex.org/W2139267459","doi":"https://doi.org/10.1109/icpp.2002.1040885","title":"Popularity-based PPM: an effective Web prefetching technique for high accuracy and low storage","display_name":"Popularity-based PPM: an effective Web prefetching technique for high accuracy and low storage","publication_year":2003,"publication_date":"2003-06-25","ids":{"openalex":"https://openalex.org/W2139267459","doi":"https://doi.org/10.1109/icpp.2002.1040885","mag":"2139267459"},"language":"en","primary_location":{"id":"doi:10.1109/icpp.2002.1040885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpp.2002.1040885","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings International Conference on Parallel Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100624798","display_name":"Xin Chen","orcid":"https://orcid.org/0009-0005-0200-2493"},"institutions":[{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]},{"id":"https://openalex.org/I267592682","display_name":"Williams (United States)","ror":"https://ror.org/007zhvp17","country_code":"US","type":"company","lineage":["https://openalex.org/I267592682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Chen","raw_affiliation_strings":["Department of Computer Science, College of William and Mary, Williamsburg, VA, USA","Department of Computer Science; College of William and Mary; Williamsburg VA USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, College of William and Mary, Williamsburg, VA, USA","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]},{"raw_affiliation_string":"Department of Computer Science; College of William and Mary; Williamsburg VA USA","institution_ids":["https://openalex.org/I16285277"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100376187","display_name":"Xiaodong Zhang","orcid":"https://orcid.org/0000-0001-8923-9293"},"institutions":[{"id":"https://openalex.org/I16285277","display_name":"William & Mary","ror":"https://ror.org/03hsf0573","country_code":"US","type":"education","lineage":["https://openalex.org/I16285277"]},{"id":"https://openalex.org/I267592682","display_name":"Williams (United States)","ror":"https://ror.org/007zhvp17","country_code":"US","type":"company","lineage":["https://openalex.org/I267592682"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaodong Zhang","raw_affiliation_strings":["Department of Computer Science, College of William and Mary, Williamsburg, VA, USA","Department of Computer Science; College of William and Mary; Williamsburg VA USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, College of William and Mary, Williamsburg, VA, USA","institution_ids":["https://openalex.org/I16285277","https://openalex.org/I267592682"]},{"raw_affiliation_string":"Department of Computer Science; College of William and Mary; Williamsburg VA USA","institution_ids":["https://openalex.org/I16285277"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.2241,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.83548283,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"280","issue":null,"first_page":"296","last_page":"304"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11478","display_name":"Caching and Content Delivery","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11478","display_name":"Caching and Content Delivery","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9980999827384949,"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/T10742","display_name":"Peer-to-Peer Network Technologies","score":0.996999979019165,"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":0.844403862953186},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.7768434286117554},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6335201263427734},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.6275913119316101},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.6116649508476257},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.48237577080726624},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.47157615423202515},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.4518449306488037},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.41448819637298584},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3573618531227112},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.27475330233573914},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1405085027217865},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08017116785049438}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.844403862953186},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.7768434286117554},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6335201263427734},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.6275913119316101},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.6116649508476257},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.48237577080726624},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.47157615423202515},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.4518449306488037},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.41448819637298584},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3573618531227112},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.27475330233573914},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1405085027217865},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08017116785049438},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpp.2002.1040885","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpp.2002.1040885","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings International Conference on Parallel Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1990322","https://openalex.org/W1506099691","https://openalex.org/W1572504775","https://openalex.org/W1645837590","https://openalex.org/W1667916464","https://openalex.org/W1971113501","https://openalex.org/W2020416126","https://openalex.org/W2026396150","https://openalex.org/W2042294443","https://openalex.org/W2049146483","https://openalex.org/W2049482525","https://openalex.org/W2066636486","https://openalex.org/W2089192108","https://openalex.org/W2089670234","https://openalex.org/W2107740482","https://openalex.org/W2111100428","https://openalex.org/W2121199344","https://openalex.org/W2134549628","https://openalex.org/W2155979007","https://openalex.org/W2161628678","https://openalex.org/W2170562663","https://openalex.org/W2911266585","https://openalex.org/W3020048185","https://openalex.org/W6600080385","https://openalex.org/W6636984794","https://openalex.org/W6637144541","https://openalex.org/W6676399765","https://openalex.org/W6758669876","https://openalex.org/W7006678390"],"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/W1985727224"],"abstract_inverted_index":{"Prediction":[0],"by":[1,37],"partial":[2],"match":[3],"(PPM)":[4],"is":[5,80,174],"a":[6,23,42,68,84,93,98,104,109,146,154,168,188],"commonly":[7],"used":[8],"technique":[9],"in":[10,22,45,87,121,140,153],"Web":[11],"prefetching,":[12],"where":[13,92],"prefetching":[14,70,200],"decisions":[15],"are":[16,118,130],"made":[17],"based":[18],"on":[19],"historical":[20],"URLs":[21,120,160],"dynamically":[24,81],"maintained":[25],"Markov":[26,63],"prediction":[27,64,195],"tree.":[28],"Existing":[29],"approaches":[30],"either":[31],"widely":[32],"store":[33,50],"the":[34,39,51,58,62,78,124,172,198],"URL":[35,95],"nodes":[36,117,129,152],"building":[38],"tree":[40,79,173],"with":[41,53,83],"fixed":[43],"height":[44,86],"each":[46,88],"branch,":[47],"or":[48],"only":[49],"branches":[52,91],"frequently":[54],"accessed":[55],"URLs.":[56],"Building":[57],"popularity":[59],"information":[60],"into":[61],"tree,":[65],"we":[66],"propose":[67],"new":[69],"model,":[71,77],"called":[72],"popularity-based":[73],"PPM.":[74],"In":[75],"this":[76,141],"updated":[82],"variable":[85],"set":[89,99,110],"of":[90,100,111,197],"popular":[94,106,119,151,159,180],"can":[96],"lead":[97],"long":[101],"branches,":[102],"and":[103,165,192],"less":[105,179],"document":[107],"leads":[108],"short":[112],"ones.":[113],"Since":[114],"majority":[115],"root":[116,147],"our":[122],"approach,":[123],"space":[125,169,190],"allocation":[126],"for":[127,163],"storing":[128],"effectively":[131],"utilized.":[132],"We":[133],"have":[134],"also":[135],"included":[136],"two":[137],"additional":[138],"optimizations":[139],"model:":[142],"(1)":[143],"directly":[144],"linking":[145],"node":[148],"to":[149,157,176],"duplicated":[150],"surfing":[155],"path":[156],"give":[158],"more":[161],"considerations":[162],"prefetching;":[164],"(2)":[166],"making":[167],"optimization":[170],"after":[171],"built":[175],"further":[177],"remove":[178],"nodes.":[181],"Our":[182],"trace-driven":[183],"simulation":[184],"results":[185],"comparatively":[186],"show":[187],"significant":[189],"reduction":[191],"an":[193],"improved":[194],"accuracy":[196],"proposed":[199],"technique.":[201]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
