Using Low-Cost Electroencephalography (Eeg) Sensor to Identify Perceived Relevance on Web Search

This poster presents preliminary results from a user study designed to evaluate the feasibility to use a low-cost EEG sensor in the identification of information relevance as perceived by users. The study involved 10 participants, both graduate and undergraduate students, performing a self-motivated exploratory search task contextualized on the literature review for their own thesis work. The study design comprised two stages that focus on (1) snippets collection and (2) explicit relevance assessments. In both stages, participants wore a low-cost electroencephalography (EEG) sensor that provides measures related to two mental states (i.e. attention and meditation). Analyses focused on comparing the presence and intensity of these mental states in the set of pages (both relevant and non-relevant) classified by the users themselves. Results showed that attention levels and blink intensity in relevant pages are significantly higher than in non-relevant ones. Copyright © 2016 by Association for Information Science and Technology