Kumar, A. "i-Seek: An Intelligent System for Eliciting and Explaining Knowledge"

Abstract

We propose i-Seek, an Intelligent System for Eliciting and Explaining Knowledge that leverages the OpenMind [1] Commonsense knowledgebase in conjunction with domainspecific knowledge in Personal Finance, Technical Help, and Health domains to act as an advisory system for novice users. Most of the interfaces are plagued by recurrent key problems: 1) elicitation " how to ask questions that enable the expert model to make decisions, and at the same time, are understandable to the novice, and 2) explanation " how to explain rationale behind expert decisions in terms that the user can understand. i-Seek maps the user's goals and expectations to the corresponding expert model's attributes as expressed in domain-specific terms. For example, instead of asking "What is your risk tolerance?", where the user might not comprehend the notion of risk tolerance, i-Seek tries to elicit the same information by asking a non-direct question such as "Do you usually buy lots of lottery tickets?". i-Seek constructs the novice user model by taking into account the user's personal information, interactions history, and the current context.