Abstract
In this paper we present a method for the automatic detection of user-stated intentions in terms of desires, purposes and commitments as specific insights deriving from the semantics of the intention expressions. The method is based on a linguistic data-driven and domain-independent framework for textual intention analysis and achieves substantial levels of accuracy in detecting future intention expressions and their structural components. Furthermore, we demonstrate several usage scenarios in the business intelligence context showing that the introduced insights can be interpreted from various perspectives and serve as variables in predictive or decision making models in any domain of interest.
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Pontiki, M., Papageorgiou, H. (2014). “There’s No Way I Would Ever Buy Any Mp3 Player with a Measly 4gb of Storage”: Mining Intention Insights about Future Actions. In: Nah, F.FH. (eds) HCI in Business. HCIB 2014. Lecture Notes in Computer Science, vol 8527. Springer, Cham. https://doi.org/10.1007/978-3-319-07293-7_23
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DOI: https://doi.org/10.1007/978-3-319-07293-7_23
Publisher Name: Springer, Cham
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