Various Approaches to Web Information Processing

Abstract

The paper focuses on the field of automatic extraction of information from texts and text document categorisation including pre-processing of text documents, which can be found on the Internet. In the frame of the presented work, we have devoted our attention to the following issues related to text categorisation: increasing the precision of categorisation algorithm results with the aid of a boosting method; searching a minimum number of decision trees, which enables the improvement of the categorisation; the influence of unlabeled data with predicted categories on categorisation precision; shortening click streams needed to access a given web document; and generation of key words related with a web document. The paper presents also results of experiments, which were carried out using the 20 News Groups and Reuters-21578 collections of documents and a collection of documents from an Internet portal of the Markiza broadcasting company.