Measuring Documents Similarity using Finite State Automata

In this paper, the similarity between a pair of text documents is measured by identifying three sets of words: words that exist in the first but not in the second, in the second but not in the first and those words that exist in both. Two deterministic finite automata are built to recognize the words of the two documents. These finite state automata are used to identify these three sets of words. An experimental study was conducted to present the proposed approach and to compare it with other peer text similarity measures: Jaccard and cosine distance. The proposed approach gave more reasonable results than Jaccard but more inflated than cosine distance approach.