Presses universitaires de Louvain onixsuitesupport@onixsuite.com 20260311T1937Z eng

COM.ONIXSUITE.9782874635045 03 01 Presses universitaires de Louvain 01 SKU 76399PDF 02 2874635049 03 9782874635045 15 9782874635045 00 ED E107 BE 10 02 11 01 02 Cahiers du CENTAL Traitement automatisé du langage 01 01 Numéro 4 Building and Exploring Web Corpora (WAC3 - 2007) Proceedings of the 3rd web as corpus workshop, incorporating cleaneval 1 B01 01 Onixsuite Contributor ID 5201 Cédrick Fairon Fairon, Cédrick Cédrick Fairon Cédrick Fairon est professeur à l'Université catholique de Louvain où il dirige le Centre de traitement automatisé du langage (CENTAL). 2 B01 01 Onixsuite Contributor ID 5580 Hubert Naets Naets, Hubert Hubert Naets 3 B01 01 Onixsuite Contributor ID 5581 Adam Kilgarriff Kilgarriff, Adam Adam Kilgarriff 4 B01 01 Onixsuite Contributor ID 5582 Gilles-Maurice de Schryver de Schryver, Gilles-Maurice Gilles-Maurice de Schryver 1 01 eng 02 eng 00 182 03 10 LAN009000 29 2012 3147 Linguistique, Sciences du langage 93 C 01 06 03 00 WACMore and more people are using Web data for linguistic and NLP research. The Web as Corpusworkshop (WAC) provides a venue for exploring how we can use it effectively and the advancementsto which this could lead.This book is a collection of the talks presented at the 3 rd WAC in Louvain-la-Neuve (Belgium).The focus is on the description of Web corpus collection projects, the exploration of Web datacharacteristics from a linguistics/NLP perspective, and on the use of crawled Web data for NLPpurposes.CLEANEVALAny use of Web data requires that it be cleaned in order to get rid of unwanted material including,for example, HTML markup, navigation bars, advertisements. To date there has been no sharingof resources or expertise in this particular domain and the cleaning has often been done minimally.Cleaneval was an exercise aimed at promoting collaboration and improving our understandingof the issues. Results and perspectives are presented in this book. 02 00 WACMore and more people are using Web data for linguistic and NLP research. The Web as Corpusworkshop (WAC) provides a venue for exploring how we can use it effectively and the advancementsto which this could lead.This book is a collection of... 03 00 WACMore and more people are using Web data for linguistic and NLP research. The Web as Corpusworkshop (WAC) provides a venue for exploring how we can use it effectively and the advancementsto which this could lead.This book is a collection of the talks presented at the 3 rd WAC in Louvain-la-Neuve (Belgium).The focus is on the description of Web corpus collection projects, the exploration of Web datacharacteristics from a linguistics/NLP perspective, and on the use of crawled Web data for NLPpurposes.CLEANEVALAny use of Web data requires that it be cleaned in order to get rid of unwanted material including,for example, HTML markup, navigation bars, advertisements. To date there has been no sharingof resources or expertise in this particular domain and the cleaning has often been done minimally.Cleaneval was an exercise aimed at promoting collaboration and improving our understandingof the issues. Results and perspectives are presented in this book. 02 00 WACMore and more people are using Web data for linguistic and NLP research. The Web as Corpusworkshop (WAC) provides a venue for exploring how we can use it effectively and the advancementsto which this could lead.This book is a collection of the... 04 00 Table of Contents .................................................................................................... vii Preface ..................................................................................................................... 1 WAC3 ..................................................................................................................... 3 Kevin P. SCANNELL, The Crúbadán Project: Corpus building for underresourced languages ..........................................................................................5 Sebastian BLOHM, Philipp CIMIANO, A Human Evaluation of Filtering Functions for Pattern-based Extraction of Arbitrary Relations from the Web .....................................................................................................................17 Emmanuel CARTIER, TextBox, a Written Corpus Tool for Linguistic Analysis ...... 33 William H. FLETCHER, Implementing a BNC-Compare-able Web Corpus ............ 43 Fabrice ISSAC, Yet Another Web Crawler ................................................................ 57 Igor LETURIA, Antton GURRUTXAGA, Iñaki ALEGRIA, Aitzol EZEIZA, CorpEus, a 'web as corpus' tool designed for the agglutinative nature of Basque ...........69 Serge SHAROFF, Classifying Web corpora into domain and genre using automatic feature identification .........................................................................83 Anil Kumar SINGH, Jagadeesh GORLA, Identification of Languages and Encodings in a Multilingual Document ............................................................. 95 CLEANEVAL .......................................................................................................... 109 Daniel BAUER, Judith DEGEN, Xiaoye DENG, Priska HERGER, Jan GASTHAUS, Eugenie GIESBRECHT, Lina JANSEN, Christin KALINA, Thorben KRÜGER, Robert MÄRTIN, Martin SCHMIDT, Simon SCHOLLER, Johannes STEGER, Egon STEMLE, Stefan EVERT, FIASCO: Filtering the Internet by Automatic Subtree Classification, Osnabrück ..................................................................... 111 Stefan EVERT, StupidOS: A high-precision approach to boilerplate removal ........ 123 Weizheng GAO, Tony ABOU-ASSALEH, GenieKnows Web Page Cleaning System ................................................................................................................. 135 Christian GIRARDI, Htmcleaner: Extracting the Relevant Text from the Web Pages ..... 141 Katja HOFMANN, Wouter WEERKAMP, Web Corpus Cleaning using Content and Structure ...................................................................................................... 145 Michal MAREK, Pavel PECINA, Miroslav SPOUSTA, Web Page Cleaning with Conditional Random Fields ............................................................................... 155 Xabier SARALEGI, Igor LETURIA, Kimatu, a tool for cleaning non-content text parts from HTML docs ....................................................................................... 163 16 00 La collection est une publication du Centre de traitement automatique du langage. Ses objectifs principaux sont de contribuer à la diffusion des travaux en linguistique et linguistique informatique et de participer à la promotion de ces disciplines. 17 00 La collection Cahiers du CENTAL est une publication du Centre de traitement automatique du langage. Ses objectifs principaux sont de contribuer à la diffusion des travaux en linguistique et linguistique informatique et de participer à la promotion de ces disciplines. 01 00 03 02 01 D502 02 198 03 125 06 890163c696bb34ad303d0ac191384de1 07 11192 https://pul.uclouvain.be/resources/titles/29303100002220/images/ff7a2112f8c3e3224ce8e3e26de1d932/THUMBNAIL/9782874635045.jpg 17 20160216T0955Z 06 3052405007518 Presses universitaires de Louvain 01 01 Dilicom PULOUVAIN 06 3052405007518 Presses universitaires de Louvain Louvain-la-Neuve BE 04 01 20070101 11 20070101 01 WORLD 02 01 GCOI 29303100002220 13 03 9782874630828 WORLD 04 03 06 3012405004818 CIACO - DUC 01 2 20 1 04 00 02 02 STD 02 9.00 01 S 24.00 7.26 1.74 EUR FI 04 00 02 02 STD 02 9.07 01 S 24.00 7.32 1.75 EUR GR 04 00 02 02 STD 02 9.00 01 S 23.00 7.32 1.68 EUR IE 04 00 02 02 STD 02 9.00 01 S 23.00 7.32 1.68 EUR PT 04 00 02 02 STD 02 9.00 01 S 22.00 7.38 1.62 EUR SI 04 00 02 02 STD 02 9.00 01 S 21.00 7.44 1.56 EUR LT 04 00 02 02 STD 02 9.00 01 S 21.00 7.44 1.56 EUR LV 04 00 02 02 STD 02 9.00 01 S 21.00 7.44 1.56 EUR NL 04 00 02 02 STD 02 9.00 01 S 21.00 7.44 1.56 EUR ES 04 00 02 02 STD 02 9.00 01 S 20.00 7.50 1.50 EUR AT 04 00 02 02 STD 02 9.00 01 S 20.00 7.50 1.50 EUR EE 04 00 02 02 STD 02 9.00 01 S 20.00 7.50 1.50 EUR MC 04 00 02 02 STD 02 9.00 01 S 20.00 7.50 1.50 EUR SK 04 00 02 02 STD 02 9.00 01 S 19.00 7.56 1.44 EUR CY 04 00 02 02 STD 02 9.00 01 S 19.00 7.56 1.44 EUR DE 04 00 02 02 STD 02 9.00 01 S 18.00 7.63 1.37 EUR MT 04 00 02 02 STD 02 9.00 01 S 8.50 8.29 0.71 EUR MQ 04 00 02 02 STD 02 9.00 01 S 8.50 8.29 0.71 EUR GP 04 00 02 02 STD 02 9.00 01 S 8.50 8.29 0.71 EUR RE 02 00 02 02 STD 02 9.00 01 R 6.00 8.49 0.51 EUR BE 04 00 02 02 STD 02 9.00 01 R 5.50 8.53 0.47 EUR FR 04 00 02 02 STD 02 9.00 01 R 4.00 8.65 0.35 EUR IT 04 00 02 02 STD 02 9.00 01 R 3.00 8.74 0.26 EUR LU 03 00 02 02 STD 02 9.00 EUR WORLD AT BE CY EE FI FR DE GR GP IE IT LV LT LU MT MQ MC NL PT RE SK SI ES