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Comparing Classifiers for Web User Intent Understanding

In: Empowering Organizations

Author

Listed:
  • 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)

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.

Suggested Citation

  • Vincenzo Deufemia & Miriam Granatello & Alessandro Merola & Emanuele Pesce & Giuseppe Polese, 2016. "Comparing Classifiers for Web User Intent Understanding," Lecture Notes in Information Systems and Organization, in: Teresina Torre & Alessio Maria Braccini & Riccardo Spinelli (ed.), Empowering Organizations, edition 1, pages 147-159, Springer.
    • Handle: RePEc:spr:lnichp:978-3-319-23784-8_12
    DOI: 10.1007/978-3-319-23784-8_12
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