Abstract
Identifying intentions of users plays a crucial role in providing better user services, such as web-search and automated message-handling. There is a significant literature on extracting speakers’ intentions and speech acts from spoken words, and this paper proposes a novel approach on extracting intentions from non-spoken words, such as web-search query texts, and text messages. Unlike spoken words, such as in a telephone conversation, text messages often contain longer and more descriptive sentences than conversational speech. In addition, text messages contain a mix of conversational speech and non-conversational contents such as documents.
The experiments describe a first attempt to extracting writers’ intentions from Usenet text messages. Messages are segmented into sentences, and then each sentence is converted into a tuple (performative, proposition) using a dialogue act classifier. The writers’ intentions are then formulated from the tuples using constraints on felicitous human communication.
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Song, I., Diederich, J. (2010). Intention Extraction from Text Messages. In: Wong, K.W., Mendis, B.S.U., Bouzerdoum, A. (eds) Neural Information Processing. Theory and Algorithms. ICONIP 2010. Lecture Notes in Computer Science, vol 6443. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17537-4_41
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DOI: https://doi.org/10.1007/978-3-642-17537-4_41
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