A Method for Measuring Sentence Similarity and Its Application to Conversational Agents

Yuhua Li, Zuhair Bandar, David McLean, and James O’Shea

This paper presents a novel algorithm for computing similarity between very short texts ofsentence length. It will introduce a method that takes account of not only semantic information but also word order information implied in the sentences. Firstly, semantic similarity between two sentences is derived from information from a structured lexical database and from corpusstatistics. Secondly, word order similarity is computed from the position of word appearance in the sentence. Finally, sentence similarity is computed as a combination of semantic similarity and word order similarity. The proposed algorithmis applied to a real world domain of conversational agents. Experimental results demonstrated that the proposed algorithm reduces the scripter’s effort to devise rule base for conversational agent.


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