Increasingly, users are interacting with information retrieval (IR) systems with the goal of
addressing complex, ill-defined search tasks. As a result, the interest in deconstructing and …

Individual differences have long been of interest in information science as they bear on the
design of information systems and services for specific populations. Yet little is known as to …

The Relevance Feedback (RF) process relies on accurate and real-time relevance
estimation of feedback documents to improve retrieval performance. Since collecting explicit …

Physiological signals can potentially be applied as objective measures to understand the
behavior and engagement of users interacting with information access systems. However …

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 …

Query augmentation is a crucial technique for refining semantically imprecise queries.
Traditionally, query augmentation relies on extracting information from initially retrieved …

Two general challenges faced by data analysis are the existence of noise and the extraction
of meaningful information from collected data. In this study, we used a multiscale framework …

The use of implicit relevance feedback from neurophysiology could deliver effortless
information retrieval. However, both computing neurophysiologic responses and retrieving …

People often have difficulty in expressing their information needs. Many times this results
from a lack of clarity about the task at hand, or the way an information or search system …

The field of neuroscience has fruitfully contributed to a wide variety of other fields, for
example, economics, marketing, and information systems, where the broad adoption and …