Deep Stock Prediction using Visual Interpretation: DeepClue
C. Durga Sruthi1, B. Dilip Kumar Reddy2

1C. Durga Sruthi, Assistant Professor, Department of CSE, GPREC, (Andhra Pradesh), India.
2B. Dilip Kumar Reddy, Assistant Professor, Department of CSE, GPREC, (Andhra Pradesh), India.
Manuscript received on 05 February 2019 | Revised Manuscript received on 27 March 2019 | Manuscript Published on 28 April 2019 | PP: 23-24 | Volume-7 Issue-5C February 2019 | Retrieval Number: E10060275C19/19©BEIESP
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Abstract: This proposed paper builds Deep Clue system that links text related models, final users using visual interpretation. We try to implement following modules in this paper. 1.Designing an architecture for a ‘deep neural network’ used for interpretation and we apply algorithms to give similar relevant factors. 2.By exploring different levels of predictive(relevant) factors and visualizing them that can be interacted by the end users at different factor-levels. Interpretation method differentiates the predicted and unpredicted values of stock price. 3.We examine visualization integrated systems using some real-world scenarios like tweeter data, financial news data and obtained stock price values by predictions. The effective working of Deep Clue helps for proper investment in stocks and to analyses tasks.
Keywords: Deep Clue, Stck Market, Text Based Visualization, Neural Network.
Scope of the Article: Visual Analytics