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

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

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    18 Citations (Scopus)

    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.
    LanguageEnglish
    Title of host publicationUnknown Host Publication
    Number of pages6
    Publication statusPublished - 2004
    EventThe 17th International FLAIRS Conference - Florida, USA
    Duration: 1 Jan 2004 → …

    Conference

    ConferenceThe 17th International FLAIRS Conference
    Period1/01/04 → …

    Fingerprint

    Semantics
    Statistics

    Cite this

    Li, Y., Bandar, Z., McLean, D., & O’Shea, J. (2004). A Method for Measuring Sentence Similarity and its Application to Conversational Agents. In Unknown Host Publication
    Li, Yuhua ; Bandar, Zuhair ; McLean, David ; O’Shea, James. / A Method for Measuring Sentence Similarity and its Application to Conversational Agents. Unknown Host Publication. 2004.
    @inproceedings{c5be8164ebe44b45b13012c4207ecf7b,
    title = "A Method for Measuring Sentence Similarity and its Application to Conversational Agents",
    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.",
    author = "Yuhua Li and Zuhair Bandar and David McLean and James O’Shea",
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    Li, Y, Bandar, Z, McLean, D & O’Shea, J 2004, A Method for Measuring Sentence Similarity and its Application to Conversational Agents. in Unknown Host Publication. The 17th International FLAIRS Conference, 1/01/04.

    A Method for Measuring Sentence Similarity and its Application to Conversational Agents. / Li, Yuhua; Bandar, Zuhair; McLean, David; O’Shea, James.

    Unknown Host Publication. 2004.

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    TY - GEN

    T1 - A Method for Measuring Sentence Similarity and its Application to Conversational Agents

    AU - Li, Yuhua

    AU - Bandar, Zuhair

    AU - McLean, David

    AU - O’Shea, James

    PY - 2004

    Y1 - 2004

    N2 - 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.

    AB - 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.

    M3 - Conference contribution

    SN - 1-57735-201-7

    BT - Unknown Host Publication

    ER -

    Li Y, Bandar Z, McLean D, O’Shea J. A Method for Measuring Sentence Similarity and its Application to Conversational Agents. In Unknown Host Publication. 2004