Interaction in information retrieval: selection and effectiveness of search terms
Journal of the American Society for Information Science
Real life, real users, and real needs: a study and analysis of user queries on the web
Information Processing and Management: an International Journal
Helping conversational agents to find informative responses: query expansion methods for chatterbots
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
Empirical Evaluation of User Models and User-Adapted Systems
User Modeling and User-Adapted Interaction
Designing and Evaluating an Adaptive Spoken Dialogue System
User Modeling and User-Adapted Interaction
Introduction to the Special Issue on Empirical Evaluation of User Models and User Modeling Systems
User Modeling and User-Adapted Interaction
Improving collaborative recommender systems by means of user profiles
Designing personalized user experiences in eCommerce
Towards a method for evaluating naturalness in conversational dialog systems
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
'Realness' in chatbots: establishing quantifiable criteria
HCI'13 Proceedings of the 15th international conference on Human-Computer Interaction: interaction modalities and techniques - Volume Part IV
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This work presents an agent-based interface that is not merely reactive to some user request, but is proactive since it is capable of engaging in a goal-directed conversation with the user, e.g., by taking the initiative to recommend new products. The naturalness of interaction, especially for casual users, is enhanced by appropriate 2D facial models. The proactiveness of the agent is based on a recommendation engine that combines content-based retrieval, which exploits user profiles based on content features extracted from the dialogue and descriptions of items that users find relevant, with collaborative filtering, which clusters users according to their expressed taste to generate recommendations within these virtual communities. The proposed system has been evaluated and validated by using a top-down approach, focusing on the system/user interaction.