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Keyword search is an effective paradigm for information discovery and has been introduced recently to query XML documents. In this paper, we address the problem of returning clustered results for keyword search on XML documents. We first propose a novel semantics for answers to an XML keyword query. The core of the
retrieval are challenges under the consideration of the aggregation of medical data is so large that it has to be stored in a cloud server. This paper proposes the similarity search tree structure to enhance the hit rate of multi-keyword ranking search. We also propose dynamic interval clustering algorithm DIK-MEDOIDS under
Mining big data often requires tremendous computational resources. This has become a major obstacle to broad applications of big data analytics. Cloud computing allows data scientists to access computational resources on-demand for building their big data analytics solutions in the cloud. However, the monetary cost of mining big data in the cloud can still be unexpectedly high. For example, running...
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