Understanding user intent on the web through interaction mining. (December 2015)

• Record Type: Journal Article
• Authors: Caruccio, Loredana; Deufemia, Vincenzo; Polese, Giuseppe
• Is Part Of: Journal of visual languages & computing. Volume 31:Part B(2016)
• Page Start: 230
• Page End: 236
• Publication Date: 2015-12
• Subjects: User intent understanding -- HCI features -- Web search -- User behavior mining -- Query classification; Visual programming languages (Computer science) -- Periodicals; Visual programming (Computer science) -- Periodicals; Programming languages (Electronic computers) -- Semantics -- Periodicals; Langages de programmation visuelle -- Périodiques; Programmation visuelle -- Périodiques; Langages de programmation -- Sémantique -- Périodiques; Programming languages (Electronic computers) -- Semantics; Visual programming (Computer science); Visual programming languages (Computer science); Periodicals; Electronic journals; 005
• DOI: 10.1016/j.jvlc.2015.10.022
• Languages: English
• ISSNs: 1045-926X

Abstract

Abstract: Predicting the goals of internet users can be extremely useful in e-commerce, online entertainment, and many other internet-based applications. One of the crucial steps to achieve this is to classify internet queries based on available features, such as contextual information, keywords and their semantic relationships. Beyond these methods, in this paper we propose to mine user interaction activities to predict the intent of the user during a navigation session. However, since in practice it is necessary to use a suitable mix of all such methods, it is important to exploit all the mentioned features in order to properly classify users based on their common intents. To this end, we have performed several experiments aiming to empirically derive a suitable classifier based on the mentioned features.