Abstract
Understanding user intent during a web navigation session is a challenging topic. Existing approaches base such activity on many different features, including HCI features, which are also used by classifiers to determine the type of a web query. In this paper we present several experiments aiming to compare the performances of main classifiers, and propose a metric to evaluate them and detect the most promising features for deriving a better classifier.
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Deufemia, V., Granatello, M., Merola, A., Pesce, E., Polese, G. (2016). Comparing Classifiers for Web User Intent Understanding. In: Torre, T., Braccini, A., Spinelli, R. (eds) Empowering Organizations. Lecture Notes in Information Systems and Organisation, vol 11. Springer, Cham. https://doi.org/10.1007/978-3-319-23784-8_12
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DOI: https://doi.org/10.1007/978-3-319-23784-8_12
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