Research at Sofia University >
S3T 2011 >
Please use this identifier to cite or link to this item:
|Title: ||News Article Classification Based on a Vector Representation Including Words’ Collocations|
|Authors: ||Kompan, Michal|
|Keywords: ||text pre-processing|
|Issue Date: ||2011|
|Publisher: ||Springer-Verlag Berlin Heidelberg 2011|
|Citation: ||Kompan, Michal, Bieliková, Mária (2011), News Article Classification Based on a Vector Representation Including Words’ Collocations, Advances in Intelligent and Soft Computing, 2011, Volume 101, Third International Conference on Software, Services and Semantic Technologies S3T 2011, September 1-3, 2011, Bourgas, Bulgaria, ISBN 978-3-642-23162-9, pp. 1-8|
|Abstract: ||In this paper we present a proposal including collocations into the pre-processing of the text mining, which we use for the fast news article recommendation and experiments based on real data from the biggest Slovak newspaper. The news article section can be predicted based on several article’s characteristics as article name, content, keywords etc. We provided experiments aimed at comparison of several approaches and algorithms including expressive vector representation, with considering most popular words collocations obtained from Slovak National Corpus.|
|Appears in Collections:||S3T 2011|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.