An Open Domain Question Answering System Based on Improved System Similarity Model

Question-answering has recently received more and more attention from researchers. It is widely regarded as the advanced stage of information retrieval. This paper provides a novel domain-independent question-answering system which is based on information retrieval in a large-scale collection of texts, and an improved system similarity model is developed and applied in it which improves the performance of the system. Many natural language processing technologies are adopted to increase the accuracy of the system. Several useful tools are incorporates as external auxiliary resources. In addition, some external knowledge such as knowledge from Internet is also widely used in this system. Test data collection and evaluation methodology from 2006 Text Retrieval Conference´s Question Answering Track are used to evaluate the system, and the results are comparatively satisfying