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
2016-01-01
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.File in questo prodotto:
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