A Rule-based Information Extraction System
Soumya Priyadarsini Panda1, Varun Behera2, Alloran Pradhan3, Abhisekh Mohanty4
1Soumya Priyadarsini Panda, Department of CSE, Silicon Institute of Technology, Bhubaneswar, India.
2Varun Behera, Department of CSE, Silicon Institute of Technology, Bhubaneswar, India.
3Alloran Pradhan, Department of CSE, Silicon Institute of Technology, Bhubaneswar, India.
4Abhisekh Mohanty, Department of CSE, Silicon Institute of Technology, Bhubaneswar, India.
Manuscript received on 30 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 1613-1617 | Volume-8 Issue-9, July 2019 | Retrieval Number: I8156078919/19©BEIESP | DOI: 10.35940/ijitee.I8156.078919
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Designing intelligent expert systems capable of answering different human queries is a challenging and emerging area of research. A huge amount of web data is available online and majority of which are in the form of unstructured documents covering articles, online news, corporate reports, medical records, social media communication data, etc. A user in need of certain information has to assess all the relevant documents to obtain the exact answer of their queries which is a time consuming and tedious work. Also, sometimes it becomes quite difficult to obtain the exact information from a list of documents quickly as and when required unless the whole document is read. This paper presents a rule-based information extraction system for unstructured web data that access the document contents quickly and provides the relevant answers to the user queries in a structured format. A number of tests were conducted to determine the overall performance of the proposed model and the results obtained in all the experiments performed shows the effectiveness of the model in providing required answers to different user queries quickly.
Keywords: Information Extraction, Information Retrieval, Multimedia Data, Natural Language Processing, Question Answering System
Scope of the Article: Expert Systems