For effectual information retrieval through Question Answering framework, it is essential to rightly reformulate the questions with respect to expected answers. We designed question answering environment model, based on question reformulation technique, in view of expected answer type for effective question answering. In the proposed model, an agent work in between the user and a semantic web based framework for question answering system and figures out how to reformulate questions to inspire the most appropriate answers. The model utilizes the criteria for “Total Answer Relevance Score” for finding the appropriate answer, returned by the framework. Analyzing the proposed model, it has been observed that the model has produced promising outcomes than the current frameworks based on question reformulation.
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