Removing Spam from Web Corpora Through Supervised Learning and Semi-manual Classification of Web Sites
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F20%3A00117841" target="_blank" >RIV/00216224:14330/20:00117841 - isvavai.cz</a>
Result on the web
<a href="https://nlp.fi.muni.cz/raslan/raslan20.pdf#page=121" target="_blank" >https://nlp.fi.muni.cz/raslan/raslan20.pdf#page=121</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Removing Spam from Web Corpora Through Supervised Learning and Semi-manual Classification of Web Sites
Original language description
Internet spam is a major issue hindering the usefulness of web corpora. Unlike traditional text corpora collected from trustworthy sources, the content of web based corpora has to be cleaned. In this paper, two experiments of non-text removal based on supervised learning are presented. First, an improvement of corpus based language analyses of selected words achieved by a supervised classifier is shown on an English web corpus. Then, a semi-manual approach of obtaining samples of non-text web pages in Estonian is introduced. This strategy makes the supervised learning process more efficient. The result spam classifiers are tuned for high recall at the cost of precision to remove as much non-text as possible. The evaluation shows the classifiers reached the recall of 71 % and 97 % for English and Estonian web corpus, respectively. A technique for avoiding spammed web sites by measuring the distance of web pages from trustworthy sites is studied too.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LM2018101" target="_blank" >LM2018101: Digital Research Infrastructure for the Language Technologies, Arts and Humanities</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the Fourteenth Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2020
ISBN
9788026316008
ISSN
2336-4289
e-ISSN
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Number of pages
11
Pages from-to
113-123
Publisher name
Tribun 2020
Place of publication
Brno
Event location
Brno
Event date
Jan 1, 2020
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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