Abstract:

Calculation of semantic similarity is an important research content of natural language processing (NLP), and many measurements have been proposed for the past few decades. These measurements have been widely used in word sense disambiguation, text clustering and other research fields. We propose a new measurement to calculate information content (IC) with WordNet ontology, and then propose two new hybrid measurements to calculate semantic similarity. Experimental results show that the proposed method is better than the existing methods for considering both the shortest path distance and the IC semantic distance simultaneously, and the results are more close to human judgment.

Key words: WordNet, semantic similarity, information content, ontology