Implementation of Question and Answering Retrieval System Over Watch Word & Head Word

Authors: Akanksha Pagare, Prof. Mohit Jain

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Abstract

In Computer Science, Question Answering System always helps to user in easier way to find the answers of given question. Information area is new area for human. With help of web crawlers, we can get any data readily available. We are only a tick far from getting to a page at remote corner of the world. We have constantly needed PCs to act savvy [1]. To achieve this undertaking the field of Artificial Intelligence appeared. One of the key obstructions in making PCs clever is comprehension of Natural Language. Normal dialect handling which manages comprehension of dialects is sub division of Artificial Intelligence. Square outline of Question Answering System is appears in beneath figure1.1. Question Answering is a great NLP application. Assignment that an inquiry noting framework acknowledges is given an inquiry and gathering of archives, finds the correct response for the question. It incorporates two integral objectives: first comprehend the different issues in normal dialect comprehension and portrayal and the second to plan regular dialect interface to PCs [2]

Introduction

Although the set of documents which are retrieved by the search engine contain a lot of information about the search topic but it may or may not contain exactly that information which the user is looking for [1].The basic idea behind the question answering system is that the users just have to enter the question and the system will retrieve the most appropriate and precise answer for that question and return it to the user. Hence in those cases where the user is looking for a short and precise answer, question answering System plays a great role rather than Search Engines, which usually provide a large set of links of those web pages which might contain the answer of that question. A typical Question Answering system can be divided into 3 modules namely: Question Processing module, Document Processing or Information Retrieval module and Answer Processing module. Each Processing and Information Retrieval module contains several sub modules and these modules use several Natural Language Processing Techniques in order to extract the proper answer. The usual Question Answering system is designed to answer simple wh-questions like “who”, “what”, “when”, “where”, etc. But the recent QA research focuses on extending the system to answer complex questions, summary questions, opinion questions etc. The paper proposes a Question Answering system that answers simple factoid, wh-questions by using a technique called Semantic Role Labeling.

Conclusion

In this paper we have proposed a framework for restricted domain question Answering System using advanced NLP tools and software. This framework can be used to develop a Question Answering System for extracting exact and precise answer from restricted domain textual data set. The proposed framework not only provides a simple and implementable framework for developing question Answering System but also provides a proper flow of data for answer extraction.