Using linguistics information for improving the sentence-based semantic relatedness measurement

This paper presents a method to measure the semantic relatedness between sentences by using conceptual graph. To compare the sentence meaning, we firstly convert an English sentence into a conceptual graph. Then we employ the conceptual graph operations to match two conceptual graphs of one sentence and another. In matching nodes in the conceptual graphs, we utilize two lexicons i.e. WordNet and VerbNet. All semantic relatedness of contents in concept nodes are computed by using WordNet. The VerbNet is another used to find the semantic relatedness of contents in conceptual relation nodes. By our specified rules, the semantic relatedness between two sentences are objectively scored. We evaluate the performance of the proposed measurement with "Microsoft Research Paraphrase Corpus". The experimental results show the % correctness as 80.00% compared to human judgment. Moreover, we apply the measurement with words sense ambiguity analysis, the proposed measurement yields 76.44% of correctness compared to human judgment.