Abstract
This paper presents a novel algorithm for computing similarity between very short texts of sentence 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 corpus statistics. 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 algorithm is 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.
| Original language | English |
|---|---|
| Title of host publication | Unknown Host Publication |
| Number of pages | 6 |
| Publication status | Published (in print/issue) - 2004 |
| Event | The 17th International FLAIRS Conference - Florida, USA Duration: 1 Jan 2004 → … |
Conference
| Conference | The 17th International FLAIRS Conference |
|---|---|
| Period | 1/01/04 → … |
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