In this paper, we describe methods for building and evaluation of limited domain question-answering characters. Several classification techniques are tested, including text classification using support vector machines, language-model based retrieval, and cross-language information retrieval techniques, with the latter having the highest success rate. We also evaluated the effect of speech recognition errors on performance with users, finding that retrieval is robust until recognition reaches over 50% WER.
Cloud computing is one of the incredible technology which enable the new vision for IT industry. Nowadays, it has become a strong alternative for startup large as well as small scale organizations that only use the resources which actually required based on pay as per use. As Cloud Computing is growing continuously and clients from different parts of the world are demanding for the various services and better outcomes, the load balancing has become the challenge for the cloud provider. To accurately manage the available resources of the different cloud provider, resources have to be properly selected according to the properties of task. Many algorithms have been proposed to provide efficient mechanisms and assigning the client's requests to available cloud nodes and aim to enhance the overall performance of the cloud and provide more satisfaction to user and efficient services. Initially this paper gives an introduction to cloud computing and load balancing. A detailed survey on different load balancing policy in cloud analyst, their advantages and drawback with obtainable solution and learn how to add new policy or customize existing load balancing policy.
There is a growing need for creating life-like virtual human simulations that can conduct a natural spoken dialog with a human student on a predefined subject. We present an overview of a spoken-dialog system that supports a person interacting with a full-size hologram-like virtual human character in an exhibition kiosk settings. We also give a brief summary of the natural language classification component of the system and describe the experiments we conducted with the system.
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