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.

Comparing Classifiers for Web User Intent Understanding

DEUFEMIA, Vincenzo;PESCE, EMANUELE;POLESE, Giuseppe
2016

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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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11386/4658483
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