Fast algorithm for assessing semantic similarity of texts

The paper presents and evaluates an efficient algorithm for measuring semantic similarity of texts. Calculating the level of semantic similarity of texts is a very difficult task and the proposed up to now methods suffer from computational complexity. This substantially limits their application area. The proposed algorithm tries to reduce the problem by merging a computationally efficient statistical approach to text analysis with a semantic component. The semantic properties of text words are extracted from the WordNet lexical database. The approach was tested using WordNets for two languages: English and Polish. The basic properties of this approach are also studied. The paper concludes with an analysis of the performance of the proposed method on a sample database and suggests some possible application areas.