Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals

Manuel Eugster, Tuukka Ruotsalo, Michiel Spape, Oswald Barral, Niklas Ravaja, Giulio Jacucci, Samuel Kaski

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

12 Sitaatiot (Scopus)
161 Lataukset (Pure)

Abstrakti

Finding relevant information from large document collections such as the World Wide Web is a common task in our daily lives. Estimation of a user’s interest or search intention is necessary to recommend and retrieve relevant information from these collections. We introduce a brain-information interface used for recommending information by relevance inferred directly from brain signals. In experiments, participants were asked to read Wikipedia documents about a selection of topics while their EEG was recorded. Based on the prediction of word relevance, the individual’s search intent was modeled and successfully used for retrieving new relevant documents from the whole English Wikipedia corpus. The results show that the users’ interests toward digital content can be modeled from the brain signals evoked by reading. The introduced brain-relevance paradigm enables the recommendation of information without any explicit user interaction and may be applied across diverse information-intensive applications.
AlkuperäiskieliEnglanti
Artikkeli38580
Sivut1-10
JulkaisuScientific Reports
Vuosikerta6
DOI - pysyväislinkit
TilaJulkaistu - 9 marraskuuta 2016
OKM-julkaisutyyppiA1 Julkaistu artikkeli, soviteltu

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