Automatic Web Page Classification
| Authors | |
|---|---|
| Year of publication | 2008 |
| Type | Article in Proceedings |
| Conference | Recent Advances in Slavonic Natural Language Processing |
| MU Faculty or unit | |
| Citation | |
| Web | https://nlp.fi.muni.cz/raslan/2008/papers/6.pdf |
| Field | Informatics |
| Keywords | automatic classification; machine learning; thesaurus |
| Description | Aim of this paper is to describe a method of automatic web page classification to semantic domains and its evaluation. The classification method exploits machine learning algorithms and several morphological as well as semantical text processing tools. In contrast to general text document classification, in the web document classification, there are often problems with short web pages. In this paper we proposed two approaches to eliminate the lack of information. In the first one we consider a wider context of a web page. That means we analyze web pages referenced from the investigated page. The second approach is based on sophisticated term clustering by their similar grammatical context. This is done using statistic corpora tool the Sketch Engine. |
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