Work place: Department of Computer Science, Shri Ramdeobaba College of Engineering and Management, Nagpur, 440013, India
Research Interests: Natural Language Processing, Artificial Intelligence and Applications
Avinash J. Agrawal received Bachelor of Engineering Degree in Computer Technology from Nagpur University, India, Master of Technology degree in Computer Technology from National Institute of Technology, Raipur, India and Ph.D. from Visvesvaraya National Institute of Technology, Nagpur, Indi in 1998, 2005 and 2013 respectively. His research area is Natural Language Processing and Databases. He is having 15 years of teaching experience. Presently he is Assistant Professor in Shri Ramdeobaba College of Engineering and Management, Nagpur. He is the author of several research papers in International and National Journal, Conferences.
DOI: https://doi.org/10.5815/ijisa.2015.12.06, Pub. Date: 8 Nov. 2015
In information retrieval, Question Answering (QA) is the task of answering a question posed in natural language (NL) using either a pre-structured database or a collection of natural language documents without human intervention. Question Answering systems are categorized on their available resource for answers. The domain specific Question Answering System gives more exact and correct answers than web based Question Answering system as it is limited for only one domain resource to answer. This paper proposes the closed domain Question Answering System for handling the legal documents of Indian Penal Code (IPC) sections and Indian Amendment Laws to retrieve more precise answers. This system tries to retrieve the exact answers from stored knowledge-base for the query related to Indian Penal Code (IPC) sections and Indian Amendment Laws asked by user. This Keyword based Question Answering System works on structured, unstructured and non-question form queries. The closed domain Question Answering system gives more accurate answer than other open domain system as it restricted single resource. Keywords from both queries and answer corpus play important role for extracting answer.[...] Read more.
DOI: https://doi.org/10.5815/ijisa.2013.12.07, Pub. Date: 8 Nov. 2013
This paper describes a method for semantic analysis of natural language queries for Natural Language Interface to Database (NLIDB) using domain ontology. Implementation of NLIDB for serious applications like railway inquiry, airway inquiry, corporate or government call centers requires higher precision. This can be achieved by increasing role of language knowledge and domain knowledge at semantic level. Also design of semantic analyzer should be such that it can easily be ported for other domains as well. In this paper a design of semantic analyzer for railway inquiry domain is reported. Intermediate result of the system is evaluated for a corpus of natural language queries collected from casual users who were not involved in the system design.[...] Read more.
Subscribe to receive issue release notifications and newsletters from MECS Press journals