Abstract
We describe here an agent-based Distributed Analytical Search (DAS) tool to search and query distributed “big data” sources regardless of data’s location, content or format. DAS semantically analyzes natural language queries from a web-based user interface. It automatically translates the query to a set of sub-queries by deploying a combination of planning and traditional database query optimization techniques. It then generates a query plan represented in XML and guide the execution by spawning intelligent agents with various types of wrappers as needed for distributed sites. The answers returned by the agents are merged appropriately and return them to the user. We have demonstrated DAS using a variety of data sources that are distributed and heterogeneous. The tool is the prime product of our company with big enterprises as our target market.
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Das, S., Ascano, R., Macarty, M. (2015). Agent-Based Distributed Analytical Search. In: Demazeau, Y., Decker, K., Bajo Pérez, J., de la Prieta, F. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Sustainability: The PAAMS Collection. PAAMS 2015. Lecture Notes in Computer Science(), vol 9086. Springer, Cham. https://doi.org/10.1007/978-3-319-18944-4_4
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DOI: https://doi.org/10.1007/978-3-319-18944-4_4
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