Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Inference networks for document retrieval
SIGIR '90 Proceedings of the 13th annual international ACM SIGIR conference on Research and development in information retrieval
Agents that reduce work and information overload
Communications of the ACM
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Toward conversational human-computer interaction
AI Magazine
IEEE Intelligent Systems
Personalizing Web Sites with Mixed-Initiative Interaction
IT Professional
Learning ontologies from natural language texts
International Journal of Human-Computer Studies
A Bayesian network approach to searching Web databases through keyword-based queries
Information Processing and Management: an International Journal - Special issue: Bayesian networks and information retrieval
The lumière project: Bayesian user modeling for inferring the goals and needs of software users
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Comparison of score metrics for Bayesian network learning
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
EHeBby: An evocative humorist chat-bot
Mobile Information Systems - Information Assurance and Advanced Human-Computer Interfaces
Semantic networks -based teachable agents in an educational game
WSEAS Transactions on Computers
Teachable characters: semantic neural networks in game AI
NN'09 Proceedings of the 10th WSEAS international conference on Neural networks
Self-organizing content management with semantic neural networks
NN'09 Proceedings of the 10th WSEAS international conference on Neural networks
Constructing composite web services from natural language requests
Web Semantics: Science, Services and Agents on the World Wide Web
ConaMSN: A context-aware messenger using dynamic Bayesian networks with wearable sensors
Expert Systems with Applications: An International Journal
Combining link and content-based information in a Bayesian inference model for entity search
Proceedings of the 1st Joint International Workshop on Entity-Oriented and Semantic Search
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As access to information becomes more intensive in society, a great deal of that information is becoming available through diverse channels. Accordingly, users require effective methods for accessing this information. Conversational agents can act as effective and familiar user interfaces. Although conversational agents can analyze the queries of users based on a static process, they cannot manage expressions that are more complex. In this paper, we propose a system that uses semantic Bayesian networks to infer the intentions of the user based on Bayesian networks and their semantic information. Since conversation often contains ambiguous expressions, the managing of context and uncertainty is necessary to support flexible conversational agents. The proposed method uses mixed-initiative interaction (MII) to obtain missing information and clarify spurious concepts in order to understand the intention of users correctly. We applied this to an information retrieval service for websites to verify the usefulness of the proposed method.