Semantic Similarity in Content-Based Filtering

Authors:
Gabriela Polcicova;Pavol Návrat
Affiliations:
-;-
Venue:
ADBIS '02 Proceedings of the 6th East European Conference on Advances in Databases and Information Systems
Year:
2002

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Abstract

In content-based filtering systems, content of items is used to recommend new items to the users. It is usually represented by words in natural language where meanings of words are often ambiguous. We studied clustering of words based on their semantic similarity. Then we used word clusters to represent items for recommending new items by content-based filtering. In the paper we present our empirical results.