A Clustering Approach to Intention Recognition
نویسندگان
چکیده
Intention recognition has significant applications in ambient intelligence, assisted living and care of the elderly, games and intrusion and other crime detection. In this chapter we explore an approach to intention recognition based on clustering. To this end we show how to map the intention recognition problem into a clustering problem. We then use three different clustering algorithms, Fuzzy C-means, Possibilistic C-means and Improved Possibilistic C-means. We illustrate and compare their effectiveness empirically using a variety of test cases, including cases involving noisy or partial data. To our knowledge the use of clustering techniques for intention recognition is novel, and this chapter suggests it is promising.
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Intention Recognition with Clustering
Intention recognition has significant applications in ambient intelligence, assisted living and care of the elderly, amongst others. In this paper we explore an approach to intention recognition based on clustering. To this end we show how to map the intention recognition problem into a clustering problem. To our knowledge the use of clustering techniques for intention recognition is novel, and...
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