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Artificially Intelligent Grid Assistant (A.I.G.A)

By Roshan Sumbaly, Abhishek Kumar, Gaurav Paruthi and Shubham Malhotra


Abstract – We present a Grid based application which works in collaboration with natural language processing (NLP), to act as a virtual assistant. The application can answer queries in a conversational manner and is capable of being deployed in various scenarios. Given the prevalence of large data sources in natural language engineering and the need for raw computational power in analysis of such data, the Grid Computing paradigm provides efficiencies and scalability otherwise unavailable to researchers. In our work we explore the integration of Grid with NLP, to mine relevant answers from these distributed resources. Our system receives queries from various interfaces and then uses NLP to understand the domain of the question. The Grid then routes the queries to the correct knowledge farm, depending on the domain found. Knowledge farms are distributed components which have large annotated domain specific datasets. We propose a novel method which involves the working of the Grid and NLP in concert to mine relevant information quickly. We have also created a working model of our system deploying various existing frameworks as our subsystems. I

Year: 2013
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