  Question answering system can be seen as the next step in information
retrieval, allowing users to pose question in natural language and receive
compact answers. For the Question answering system to be successful, research
has shown that the correct classification of question with respect to the
expected answer type is requisite. We propose a novel architecture for question
classification and searching in the index, maintained on the basis of expected
answer types, for efficient question answering. The system uses the criteria
for Answer Relevance Score for finding the relevance of each answer returned by
the system. On analysis of the proposed system, it has been found that the
system has shown promising results than the existing systems based on question
classification.
