Refining Diagnostic POMDPs with User Feedback
نویسندگان
چکیده
Bayesian networks have been widely used for diagnostics. These models can be extended to POMDPs to select the best action. This allows modeling partial observability due to causes and the utility of executing various tests. We describe the problem of refining diagnostic POMDPs when user feedback is available. We propose utilizing user feedback to pose constraints on the model, i.e., the transition, observation and reward functions. These constraints can then be used to efficiently learn the POMDP model and incorporate expert knowledge about the problem.
منابع مشابه
Query expansion based on relevance feedback and latent semantic analysis
Web search engines are one of the most popular tools on the Internet which are widely-used by expert and novice users. Constructing an adequate query which represents the best specification of users’ information need to the search engine is an important concern of web users. Query expansion is a way to reduce this concern and increase user satisfaction. In this paper, a new method of query expa...
متن کاملImproving controllability and predictability of an interactive user model driven search interface
In this extended abstract, we discuss user controllability and system predictability in the context of exploratory search. When a user is directing a search engine by interactively refining a probabilistic user model using uncertain relevance feedback, usability problems regarding controllability and predictability may arise. By interpreting user’s actions as setting a goal for an optimization ...
متن کاملWeb pages ranking algorithm based on reinforcement learning and user feedback
The main challenge of a search engine is ranking web documents to provide the best response to a user`s query. Despite the huge number of the extracted results for user`s query, only a small number of the first results are examined by users; therefore, the insertion of the related results in the first ranks is of great importance. In this paper, a ranking algorithm based on the reinforcement le...
متن کاملBandwidth and Delay Optimization by Integrating of Software Trust Estimator with Multi-User Cloud Resource Competence
Trust Establishment is one of the significant resources to enhance the scalability and reliability of resources in the cloud environment. To establish a novel trust model on SaaS (Software as a Service) cloud resources and to optimize the resource utilization of multiple user requests, an integrated software trust estimator with multi-user resource competence (IST-MRC) optimization mechanism is...
متن کاملRelevance Feedback based on Query Refining and Feature Database Updating in CBIR System
Relevance feedback (RF), which introduces human visual perception into the retrieval process gradually, is an efficient improvement for narrowing down the gap between low-level visual feature representation of an image and its semantic meaning in content-based image retrieval (CBIR). In this paper, a new relevance feedback approach based on query refining and feature database updating in CBIR s...
متن کامل