Semantics-Enhanced Answer Selection in Closed-domain Question Answering System

In the rapid growing and dynamic world, Information Retrieval is a paramount task. Though efficient Information Retrieval Systems exist, the advent of advanced computing techniques such as Artificial Intelligence impose a need to have more intelligent IR systems that can actually understand user queries. Interpreting user queries is also another major challenge in question answering systems. The proposed system is such an intelligent IR system that semantically extends and understands user queries to produce more accurate and relevant information. This model is useful to organizations or universities which employs this question answering system to answer user or student queries. This can be done by feeding information into a knowledge base, where the query data or the relevant information is retrieved. But what lacks in most of the question answering systems is its accuracy and precision in answering to the queries. Information retrieval is the major task in question answering systems.