A talk on “Proactive contextual information retrieval” by Samuel Kaski of Aalto University and University of Helsinki, Finland.

Abstract:

In proactive information retrieval the ultimate goal is to seamlessly access relevant multimodal information in a context-sensitive way. Usually explicit queries are not available or are insufficient, and the alternative is to try to infer users’ interests from implicit feedback signals, such as clickstreams or eye tracking. We have studied how to infer relevance of texts and images to the user from the eye movement patterns. The interests, formulated as an implicit query, can then be used in further searches. I will discuss our new machine learning-based results in this field, including data glasses-based augmented reality interface to contextual information, and timeline browsers for life logs.

Biography:

Prof. Samuel Kaski, D.Sc. (PhD), is Director of Helsinki Institute for Information Technology HIIT, vice director of Finnish Centre of Excellence in Computational Inference Research COIN, and director of Finnish Doctoral Programme in Computational Sciences FICS. He studies statistical machine learning, proactive interfaces and computational biology.