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To utilize users’ relevance feedback is a significant and challenging issue in content-based image retrieval due to its capability of narrowing the “semantic gap” between the low-level features and the higher-level concepts. This paper proposes a novel relevance feedback framework for image retrieval based on Ant Colony algorithm, by accumulating users’ feedback to construct a “hidden” semantic network...
Mining closed frequent item set(CFI) plays a fundamental role in many real-world data mining applications. However, memory requirement and computational cost have become the bottleneck of CFI mining algorithms, particularly when confronting with large scale datasets, which herewith makes mining closed frequent item set from large scale datasets a significant and challenging issue. To address the above...
Mining closed frequent itemset (CFI) plays an essential role in many real-world data mining applications. With the emergence of abundant large-scale data sets, it now turns to be a significant and challenging issue to mine CFI concurrently. This paper proposes a parallel balanced mining algorithm for CFI based on the MapReduce platform. The proposed algorithm adopts Greedy strategy to group items...
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