Intention extraction from text messages

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.