Comparing Classifiers for Web User Intent Understanding

Vincenzo Deufemia (), Miriam Granatello (), Alessandro Merola (), Emanuele Pesce () and Giuseppe Polese ()
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Vincenzo Deufemia: Università Di Salerno
Miriam Granatello: Università Di Salerno
Alessandro Merola: Università Di Salerno
Emanuele Pesce: Università Di Salerno
Giuseppe Polese: Università Di Salerno

A chapter in Empowering Organizations, 2016, pp 147-159 from Springer

Abstract: 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.

Keywords: User intent understanding; HCI features; Web search (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-319-23784-8_12

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DOI: 10.1007/978-3-319-23784-8_12

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