{"id":"https://openalex.org/W104909239","doi":"https://doi.org/10.1137/1.9781611972801.81","title":"A Generalized Tree Matching Algorithm Considering Nested Lists for Web Data Extraction","display_name":"A Generalized Tree Matching Algorithm Considering Nested Lists for Web Data Extraction","publication_year":2010,"publication_date":"2010-04-29","ids":{"openalex":"https://openalex.org/W104909239","doi":"https://doi.org/10.1137/1.9781611972801.81","mag":"104909239"},"language":"en","primary_location":{"id":"doi:10.1137/1.9781611972801.81","doi":"https://doi.org/10.1137/1.9781611972801.81","is_oa":false,"landing_page_url":"https://doi.org/10.1137/1.9781611972801.81","pdf_url":null,"source":{"id":"https://openalex.org/S4306420871","display_name":"SIAM International Conference on Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2010 SIAM International Conference on Data Mining","raw_type":"proceedings-article"},"volume":null,"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/A5110576904","display_name":"Nitin Jindal","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nitin Jindal","raw_affiliation_strings":["University of Illinois at Chicago"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039448597","display_name":"Bing Liu","orcid":"https://orcid.org/0000-0003-2874-2746","observed_orcids":["https://orcid.org/0000-0003-2874-2746"]},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bing Liu","raw_affiliation_strings":["University of Illinois at Chicago"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I39422238"],"apc_list":null,"apc_paid":null,"fwci":3.1447,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.92849836,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"930","last_page":"941"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":1.0,"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":1.0,"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/T10538","display_name":"Data Mining Algorithms and Applications","score":0.0,"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/T14435","display_name":"Information Retrieval and Data Mining","score":0.0,"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/tree-matching","display_name":"tree matching","score":0.9599999785423279},{"id":"https://openalex.org/keywords/web-scraping","display_name":"web scraping","score":0.8960000276565552},{"id":"https://openalex.org/keywords/nested-lists","display_name":"nested lists","score":0.9649999737739563},{"id":"https://openalex.org/keywords/structured-information-extraction","display_name":"structured data extraction","score":0.6790000200271606},{"id":"https://openalex.org/keywords/grammar-generation","display_name":"grammar generation","score":0.9409999847412109},{"id":"https://openalex.org/keywords/repeated-patterns","display_name":"repeated patterns","score":0.6890000104904175},{"id":"https://openalex.org/keywords/pattern-generation","display_name":"pattern generation","score":0.35600000619888306},{"id":"https://openalex.org/keywords/website-templates","display_name":"web templates","score":0.3709999918937683}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7448914647102356},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.6567197442054749},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6177504658699036},{"id":"https://openalex.org/C21959979","wikidata":"https://www.wikidata.org/wiki/Q36774","display_name":"Web page","level":2,"score":0.5813838243484497},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.5719963312149048},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5518114566802979},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.46725982427597046},{"id":"https://openalex.org/C103000020","wikidata":"https://www.wikidata.org/wiki/Q1978426","display_name":"Nested set model","level":3,"score":0.437327116727829},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43537700176239014},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3440331220626831},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32397282123565674},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17852306365966797},{"id":"https://openalex.org/C5655090","wikidata":"https://www.wikidata.org/wiki/Q192588","display_name":"Relational database","level":2,"score":0.11449339985847473},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.1036616861820221},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1137/1.9781611972801.81","doi":"https://doi.org/10.1137/1.9781611972801.81","is_oa":false,"landing_page_url":"https://doi.org/10.1137/1.9781611972801.81","pdf_url":null,"source":{"id":"https://openalex.org/S4306420871","display_name":"SIAM International Conference on Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2010 SIAM International Conference on Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.187.3058","doi":null,"is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.187.3058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.siam.org/proceedings/datamining/2010/dm10_081_jindaln.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1515087027","https://openalex.org/W1519606823","https://openalex.org/W1553019137","https://openalex.org/W1592635378","https://openalex.org/W1969005071","https://openalex.org/W1975009259","https://openalex.org/W2013725398","https://openalex.org/W2015551056","https://openalex.org/W2034797903","https://openalex.org/W2049461910","https://openalex.org/W2054658115","https://openalex.org/W2065568440","https://openalex.org/W2069388662","https://openalex.org/W2072489225","https://openalex.org/W2088600132","https://openalex.org/W2093559286","https://openalex.org/W2096496923","https://openalex.org/W2101909884","https://openalex.org/W2102694093","https://openalex.org/W2104086170","https://openalex.org/W2106235201","https://openalex.org/W2116493296","https://openalex.org/W2127855221","https://openalex.org/W2128341918","https://openalex.org/W2129595335","https://openalex.org/W2133669904","https://openalex.org/W2135479443","https://openalex.org/W2136753314","https://openalex.org/W2143309843","https://openalex.org/W2150721933","https://openalex.org/W2153072229","https://openalex.org/W2154444297","https://openalex.org/W2157160236","https://openalex.org/W2160196229","https://openalex.org/W2364964713"],"related_works":["https://openalex.org/W2381136900","https://openalex.org/W2187337573","https://openalex.org/W4238878237","https://openalex.org/W1488854785","https://openalex.org/W2365499193","https://openalex.org/W2075100598","https://openalex.org/W1966511940","https://openalex.org/W2376787882","https://openalex.org/W2061189702","https://openalex.org/W1993141752"],"abstract_inverted_index":{"This":[0,132],"paper":[1,133],"studies":[2],"structured":[3],"data":[4,129,192,217],"extraction":[5,130],"from":[6,22],"Web":[7,50,191],"pages.":[8],"One":[9],"of":[10,32,57,77,163,216],"the":[11,49,64,74,78,88,94,148,161,168,202,220,254,258],"effective":[12],"methods":[13],"is":[14,37,167,174,182,243],"tree":[15,34,125,137,144,170],"matching,":[16],"which":[17],"can":[18,80,99],"detect":[19,118],"template":[20,90],"patterns":[21],"web":[23],"pages":[24,200],"used":[25],"for":[26,190,262],"extraction.":[27],"However,":[28],"one":[29],"major":[30],"limitation":[31],"existing":[33,112,143,260],"matching":[35,126,138,145,171],"algorithms":[36],"their":[38],"inability":[39],"to":[40,63,117,127,150,176,245],"deal":[41],"with":[42,45,147],"embedded":[43],"lists":[44,52,56,67,102,120,153,215],"repeated":[46],"patterns.":[47,131],"In":[48,179],"context,":[51],"are":[53,186,233],"everywhere,":[54],"e.g.,":[55],"products,":[58],"jobs":[59],"and":[60,122,205],"publications.":[61],"Due":[62],"fact":[65],"that":[66,173,184,253],"in":[68,103],"trees":[69,79],"may":[70,225],"have":[71,100],"different":[72,228,237],"lengths,":[73],"match":[75],"score":[76],"be":[81],"very":[82],"low":[83],"although":[84],"they":[85],"follow":[86],"exactly":[87],"same":[89,203,221],"pattern.":[91],"To":[92,108,160],"make":[93],"matter":[95],"worse,":[96],"a":[97,135,155,211,227],"list":[98,224],"nested":[101,152],"it":[104,181],"at":[105],"any":[106],"level.":[107],"solve":[109,246],"this":[110,166],"problem,":[111],"research":[113],"uses":[114],"various":[115],"heuristics":[116],"candidate":[119],"first":[121,169],"then":[123],"applies":[124],"generate":[128],"proposes":[134],"generalized":[136],"algorithm":[139,146,172,242,256],"by":[140],"extending":[141],"an":[142],"ability":[149],"handle":[151],"through":[154],"novel":[156],"grammar":[157],"generation":[158,196,208],"algorithm.":[159],"best":[162],"our":[164],"knowledge,":[165],"able":[175,244],"consider":[177],"lists.":[178],"addition,":[180],"well-known":[183],"there":[185],"two":[187,231],"problem":[188],"formulations":[189],"extraction:":[193],"(1)":[194],"pattern":[195,207],"based":[197,209],"on":[198,210],"multiple":[199],"following":[201,219],"template,":[204],"(2)":[206],"single":[212],"page":[213],"containing":[214],"instances":[218],"templates":[222],"(each":[223],"use":[226],"template).":[229],"These":[230],"problems":[232,248,264],"currently":[234],"solved":[235],"using":[236],"algorithms.":[238],"The":[239],"proposed":[240],"(single)":[241],"both":[247,263],"effectively.":[249],"Extensive":[250],"experiments":[251],"show":[252],"new":[255],"outperforms":[257],"state-of-the-art":[259],"systems":[261],"considerably.":[265]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":4},{"year":2012,"cited_by_count":5}],"updated_date":"2026-10-05T09:50:58.205359","created_date":"2016-06-24T00:00:00"}