Improving Retrieval Accuracy in Main Content Extraction from HTML Web Documents

Improving Retrieval Accuracy in Main Content Extraction from HTML Web Documents

The rapid growth of text based information on the World Wide Web and various applications making use of this data motivates the need for efficient and effective methods to identify and separate the “main content” from the additional content items, such as navigation menus, advertisements, design ele...

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Bibliographic Details
Main Author: Mohammadzadeh, Hadi
Other Authors: Universität Leipzig, Abteilung Automatische Sprachverarbeitung
Format: Doctoral Thesis
Language:English
Published: Universitätsbibliothek Leipzig 2013
Subjects:
Hauptinhalt Extraktion
Information Retrieval
UTF-8-Kodierung Form
HTML-Dokumente
rechts nach links
Sprachen
Web Mining
Unicode-Zeichensatz
Vektorraummodell
Cosinus-Ähnlichkeit
überlappen erzielte Ähnlichkeit
Schlagzeile Extraktion
Titel Extraktion
Trend-Mining
main content extraction
information retrieval
UTF-8 encoding form
HTML documents
right to left languages
web mining
Unicode character set
vector space model
cosine similarity
overlap scoring similarity
headline extraction
title extraction
trend mining
ddc:500
Online Access:http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-130500
http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-130500
http://www.qucosa.de/fileadmin/data/qucosa/documents/13050/Thesis-Hadi-Mohammadzadeh.pdf

Internet

http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-130500
http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-130500
http://www.qucosa.de/fileadmin/data/qucosa/documents/13050/Thesis-Hadi-Mohammadzadeh.pdf

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