{"id":"https://openalex.org/W2140018945","doi":"https://doi.org/10.1145/1772690.1772753","title":"A pattern tree-based approach to learning URL normalization rules","display_name":"A pattern tree-based approach to learning URL normalization rules","publication_year":2010,"publication_date":"2010-04-26","ids":{"openalex":"https://openalex.org/W2140018945","doi":"https://doi.org/10.1145/1772690.1772753","mag":"2140018945"},"language":"en","primary_location":{"id":"doi:10.1145/1772690.1772753","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1772690.1772753","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th international conference on World wide web","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/A5030752617","display_name":"Tao Le\u00ed","orcid":"https://orcid.org/0000-0002-0900-1582"},"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":false,"raw_author_name":"Tao Lei","raw_affiliation_strings":["Peking Univ., Beijing, China","Peking University, Beijing, China#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking Univ., Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Peking University, Beijing, China#TAB#","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069272117","display_name":"Rui Cai","orcid":"https://orcid.org/0000-0002-6499-2091"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Cai","raw_affiliation_strings":["Microsoft Research, Asia, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research, Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002360117","display_name":"Jiang-Ming Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiang-Ming Yang","raw_affiliation_strings":["Microsoft Research, Asia, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research, Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039611523","display_name":"Ke Yan","orcid":"https://orcid.org/0000-0002-1611-6636"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yan Ke","raw_affiliation_strings":["Microsoft Corporation, Redmond, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023978319","display_name":"Xiaodong Fan","orcid":"https://orcid.org/0000-0002-6499-7319"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaodong Fan","raw_affiliation_strings":["Microsoft Corporation, Redmond, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Corporation, Redmond, WA, USA","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100637600","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0002-8092-3459"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["Microsoft Research, Asia, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research, Asia, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.709,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.96213141,"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":"611","last_page":"620"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9993000030517578,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.8384292721748352},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.6967955231666565},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6185518503189087},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.6183859705924988},{"id":"https://openalex.org/keywords/crawling","display_name":"Crawling","score":0.5972207188606262},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4916849732398987},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4698920249938965},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4471094608306885},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38824355602264404},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3654593229293823}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8384292721748352},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.6967955231666565},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6185518503189087},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.6183859705924988},{"id":"https://openalex.org/C100368936","wikidata":"https://www.wikidata.org/wiki/Q1411725","display_name":"Crawling","level":2,"score":0.5972207188606262},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4916849732398987},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4698920249938965},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4471094608306885},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38824355602264404},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3654593229293823},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","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},{"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/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"score":0.0},{"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/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1772690.1772753","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1772690.1772753","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th international conference on World wide web","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":18,"referenced_works":["https://openalex.org/W1965415591","https://openalex.org/W1986968077","https://openalex.org/W2012833704","https://openalex.org/W2016746605","https://openalex.org/W2038276547","https://openalex.org/W2040482385","https://openalex.org/W2046166587","https://openalex.org/W2049955619","https://openalex.org/W2066636486","https://openalex.org/W2067432306","https://openalex.org/W2085922539","https://openalex.org/W2097184821","https://openalex.org/W2112104357","https://openalex.org/W2145349611","https://openalex.org/W2152565070","https://openalex.org/W2257424246","https://openalex.org/W4241558715","https://openalex.org/W4254697110"],"related_works":["https://openalex.org/W4393220254","https://openalex.org/W4321258516","https://openalex.org/W2051833850","https://openalex.org/W4287845917","https://openalex.org/W3156164993","https://openalex.org/W2385015894","https://openalex.org/W2171573941","https://openalex.org/W4317382653","https://openalex.org/W2165684222","https://openalex.org/W1979757569"],"abstract_inverted_index":{"Duplicate":[0],"URLs":[1,26,152,240],"have":[2],"brought":[3],"serious":[4],"troubles":[5],"to":[6,17,23,27,83,132,168,189],"the":[7,55,60,98,176,179,184,191,220,246],"whole":[8],"pipeline":[9],"of":[10,34,66,76,90,100,151,255],"a":[11,28,32,67,73,104,109,148,158,163,171],"search":[12,68],"engine,":[13],"from":[14,103,117,139,182,216,241],"crawling,":[15],"indexing,":[16],"result":[18],"serving.":[19],"URL":[20,38,101,172],"normalization":[21,39,102],"is":[22,46,114,187,201],"transform":[24],"duplicate":[25,91,130,155,239],"canonical":[29],"form":[30],"using":[31],"set":[33,150],"rewrite":[35,85,124],"rules.":[36],"Nowadays":[37],"has":[40],"attracted":[41],"significant":[42],"attention":[43],"as":[44,204],"it":[45],"lightweight":[47],"and":[48,59,107,136,143,196,230,259],"can":[49],"be":[50],"flexibly":[51],"integrated":[52],"into":[53,154],"both":[54,256],"online":[56],"(e.g.":[57,62],"crawling)":[58],"offline":[61],"index":[63],"compression)":[64],"parts":[65],"engine.":[69],"To":[70],"deal":[71],"with":[72],"large":[74],"scale":[75],"websites,":[77],"automatic":[78],"approaches":[79,122],"are":[80,144,206],"highly":[81],"desired":[82],"learn":[84,123],"rules":[86,125,205,226],"for":[87,157],"various":[88],"kinds":[89],"URLs.":[92],"In":[93,214],"this":[94],"paper,":[95],"we":[96,161],"rethink":[97],"problem":[99],"global":[105],"perspective":[106],"propose":[108],"pattern":[110,173,177,211,221],"tree-based":[111],"approach,":[112],"which":[113],"remarkably":[115],"different":[116],"existing":[118],"approaches.":[119],"Most":[120],"current":[121],"by":[126,227],"iteratively":[127],"inducing":[128],"local":[129],"pairs":[131],"more":[133,194,235],"general":[134],"forms,":[135],"inevitably":[137],"suffer":[138],"noisy":[140],"training":[141,149,185],"data":[142],"practically":[145],"inefficient.":[146],"Given":[147],"partitioned":[153],"clusters":[156],"targeted":[159],"website,":[160],"develop":[162],"simple":[164],"yet":[165],"efficient":[166],"algorithm":[167],"automatically":[169],"construct":[170],"tree.":[174],"With":[175],"tree,":[178],"statistical":[180],"information":[181],"all":[183],"samples":[186],"leveraged":[188],"make":[190],"learning":[192,199],"process":[193,200],"robust":[195],"reliable.":[197],"The":[198],"also":[202],"accelerated":[203],"directly":[207],"summarized":[208],"based":[209],"on":[210,234],"tree":[212,222],"nodes.":[213],"addition,":[215],"an":[217],"engineering":[218],"perspective,":[219],"helps":[223],"select":[224],"deployable":[225],"removing":[228],"conflicts":[229],"redundancies.":[231],"An":[232],"evaluation":[233],"than":[236],"70":[237],"million":[238],"200":[242],"websites":[243],"showed":[244],"that":[245],"proposed":[247],"approach":[248],"achieves":[249],"very":[250],"promising":[251],"performance,":[252],"in":[253],"terms":[254],"de-duping":[257],"effectiveness":[258],"computational":[260],"efficiency.":[261]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
