Abstract

The graphical user interface has been the predominate user interface in web and software applications with the interaction primarily being click-driven. Advances in Natural Language Understanding (NLU) are leading the transition to user interfaces that are conversation-driven using natural language. Utilizing a state-of-the-art open source framework with NLU capabilities, we demonstrate and illustrate a conversational user interface for Stock Analysis based on real-time computation for processing textual and numerical data. The key features of the proposed system incorporates real-time stock price retrieval, latest financial news, historical graphs of stock prices, stock sentiment based on tweets, and forecasting stock price for companies. We further explore a generalized on-demand model rendering for stock prediction using a type of Recurrent Neural Network called Long Short-Term Memory, with experimentation on model hyperparameters.

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