Abstract
Human centred services are increasingly common in the market of mobile devices. However, affective aware services are still scarce. In turn, the recognition of secondary emotions in mobility conditions is critical to develop affective aware mobile applications. The emerging field of Affective Computing offers a few solutions to this problem. We propose a method to deduce user’s secondary emotions based on context and personal profile. In a realistic environment, we defined a set of emotions common to a museum visit. Then we developed a context aware museum guide mobile application. To deduce affective states, we first used a method based on the user profile solely. Enhancement of this method with machine learning substantially improved the recognition of affective states. Implications for future work are discussed.
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Acknowledgments
We thank our students (A. Fatiol, O.Litan, R.M. Cimpean, E. Ciurea, M. Herculea) for their help in developing the web based and the J2ME application and to all participants in the tests.
This work benefit by the support of the national contract PN2 Idei number 1062 and CNCSIS type A number 1566.
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Benţa, KI., Cremene, M., Gibă, N.R., Eligio, U.X., Rarău, A. (2010). Secondary Emotions Deduction from Context. In: Sobh, T. (eds) Innovations and Advances in Computer Sciences and Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3658-2_29
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DOI: https://doi.org/10.1007/978-90-481-3658-2_29
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