Abstract
The goal of Information Retrieval (IR) systems is to satisfy searchers' Information Need (IN). Our research focuses on next-generation IR engines, which can proactively detect, identify, and serve INs without receiving explicit queries. It is essential, therefore, to be able to detect when INs occur. Previous research has established that a realisation of INs physically manifests itself with specific brain activity. With this work we take the next step, showing that monitoring brain activity can lead to accurate predictions of a realisation of IN occurrence. We have conducted experiments whereby twenty-four participants performed a Q/A Task, while their brain activity was being monitored using functional Magnetic Resonance Imaging (fMRI) technology. The questions were selected and developed from the TREC-8 and TREC 2001 Q/A Tracks. We present two methods for predicting the realisation of an IN, i.e. Generalised method (GM) and Personalised method (PM). GM is based on the collective brain activity of all twenty-four participants in a predetermined set of brain regions known to be involved in representing a realisation of INs. PM is unique to each individual and employs a 'Searchlight' analysis to locate brain regions informative for distinguishing when a “specific” user realises an information need. The results of our study show that both methods were able to predict a realisation of an IN (statistically) significantly better than chance. Our results also show that PM (statistically) significantly outperformed GM in terms of prediction accuracy. These encouraging findings make the first fundamental step towards proactive IR engines based on brain signals.
Highlights
Information need (IN) is an essential concept and plays a core and fundamental role in the information seeking and retrieval process
We aim to train a classification model on brain activity to be able to discriminate between an IN realisation vs memory retrieval, within an Information Retrieval (IR) process performed by participants engaged in a Question Answering (Q/A) retrieval task
This paper indicates that the period of IN involves complex patterns of brain activity and by application of more sensitive data analyses, reliable fine patterns of brain activity that are consistent with being in a state of IN can be revealed
Summary
Information need (IN) is an essential concept and plays a core and fundamental role in the information seeking and retrieval process. Over the last several decades, much research has been dedicated to better understand IN to most effectively satisfy it with information retrieval engines, e.g. Satisfying INs is a formidable challenge due to the inherent complexity and ambiguity associated with the IN concept. That is, expressing an IN using a set of query keywords is an uncertain and noisy process [53], as keywords can only vaguely approximate the actual IN [51]. It is possible that a given query may not sufficiently define the characteristics of relevant documents, or even any relevant information since a searcher cannot form an appropriate initial state from which to form a query [13]
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