Text Classification Using Fuzzy Neural Network
U. Sree Krishna1, Hima Shree2, K. Jayadeep3, P. Lakshmi Prasanna4
1U. Sree Krishna, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
2Hima Shree, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
3K. Jayadeep, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
3P. Lakshmi Prasanna, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur (Andhra Pradesh), India.
Manuscript received on 23 April 2019 | Revised Manuscript received on 05 May 2019 | Manuscript Published on 17 May 2019 | PP: 193-198 | Volume-7 Issue-6S4 April 2019 | Retrieval Number: F10370476S419/2019©BEIESP
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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: In today’s world, Large documents are being produced every day which require to be organized and also have the ability to extract the data of out of them. This organization into various topics is known as text classification. To perform text classification, many efficient algorithms are available, but this paper will focus on Text classification using Fuzzy Neural Networks. The First step in the algorithm that we chose is preprocessing. In this step, all the words are divided into tokens and stop words are removed along with the stemming also being done. The next step in this process in feature extraction, this process selects a subset of key words which best represent the text documents to be able to classify the document properly. The process however cannot yield 100% accuracy but has been refined in the modern-day world up to 94%.
Keywords: Text Classification, Neural Networks, Fuzzy, Documents, Decision Tree.
Scope of the Article: Fuzzy Logics