Data perturbation is a popular technique for privacypreserving data mining. The major challenge of data perturbation is balancing privacy protection and data quality, which are no...
Enhancing the service-oriented architecture paradigm with semantic components is a new field of research and goal of many ongoing projects. The results lead to more powerful web a...
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
Event-based summarization attempts to select and organize the sentences in a summary with respect to the events or the sub-events that the sentences describe. Each event has its o...
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
T. Ravindra Babu, M. Narasimha Murty, Vijay K. Agr...