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Distributed Learning over Massive XML Documents in ELM Feature Space
2015
Mathematical Problems in Engineering
With the exponentially increasing volume of XML data, centralized learning solutions are unable to meet the requirements of mining applications with massive training samples. In this paper, a solution to distributed learning over massive XML documents is proposed, which provides distributed conversion of XML documents into representation model in parallel based on MapReduce and a distributed learning component based on Extreme Learning Machine for mining tasks of classification or clustering.
doi:10.1155/2015/923097
fatcat:2qxlvlx2pfesbnsgxzsgaplaea