Designing interfaces for guided collection of knowledge about everyday objects from volunteers

A new generation of intelligent applications can be enabled by broad-coverage knowledge repositories about everyday objects. We distill lessons in design of intelligent user interfaces which collect such broad-coverage knowledge from untrained volunteers. We motivate the knowledge-driven template-based approach adopted in LEARNER2, a second generation proactive acquisition interface for eliciting such knowledge. We present volume, accuracy, and recall of knowledge collected by fielding the system for 5 months. LEARNER2 has so far acquired 99,018 general statements, emphasizing knowledge about parts of and typical uses of objects. Categories and Subject Descriptors: I.2.6 [Artificial Intelligence]: Learning – knowledge acquisition; I.2.4 Knowledge Representation Formalisms and Methods: frames and scripts, semantic networks General Terms: Algorithms, Design, Experimentation, Human Factors.

• Type: Conference
• Year: 2005
• Where: IUI
• Authors: Timothy Chklovski
• Keywords: Broad-coverage Knowledge, Broad-coverage Knowledge Repositories, IUI 2005, Knowledge Representation Formalisms And Methods, Software Engineering