GWC 2008

SemanticNet: a WordNet-based Tool for the Navigation of Semantic… 29
3.2 Evaluation of the Information
Concerning the information added in the SemanticNet we have to distinguish between
information gathered from WordNet and information extracted from Wikipedia
documents. Properties of the information coming from WordNet are maintained in the
structure used in the SemanticNet. Then we add new terms by means of a phase of
classification of Wikipedia documents, in order to identify correctly information
added in the map of concept.
As we said, COMMONSENSE relations added in the SN are the links contained in
the Wikipedia pages related to a particular sense of a term. The main question is to
identify which categories are associated with that specific sense. We conducted our
tests on sets of documents, extracted from a total set of 47639 documents and
evaluating only 5 categories : Plants, Medicine, Animals, Geography and Chemistry.
In the evaluation we only consider if the classified document belongs or not to the
specified category. The Classifier assigns a number of possible categories to each
document with a weight associated. We selected the best result for each document by
means of a minimum level of weight. In this way all terms added to the SemanticNet
are always related in the correct way with others.
Fig. 2: Classified documents for each category
In Fig.3 the measures of the Classifier about 5 categories are showed. Results are
validated by hand verifying all documents identified by the Classifier for each
category.
Fig. 3: Measures of the classification