A Novel Architecture For Question Classification Based Indexing Scheme For Efficient Question Answering
This addresses the need for accurate question classification in information retrieval systems, but it appears incremental as it builds on existing methods for question answering.
The paper tackles the problem of question classification for efficient question answering by proposing a novel architecture that uses an indexing scheme based on expected answer types, showing promising results compared to existing systems.
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.