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A novel exploration-exploitation strategy for reinforcement learning (RL) based an adaptive ant colony system is proposed in this paper, which called AACO-RL. The elitist strategy ant system (ASelitist), developing from ant system, presented by M. Dorigo, improved efficiency through imposing additional pheromone on the paths of the global optimal solution. But as the amount of elitist ant is produced...
According to this paper, a novel approach based on non-linear support vetor machine decision tree (NSVMDT) and K nearest neighbors (KNN) is proposed towards Chinese text categorization. To begin with, SVM is extended to non-linear SVM by using kernel functions. And then the method of NSVMDT is presented based on traditional SVM decision tree. Furthermore, the KNN is combined with NSVMDT to solve the...
A new hierarchical distributed P2P architecture and clustering algorithm (HDP2PA) is proposed in this paper. HP2PA can address the problems of large central storage requirement in centralized data mining and heavy traffic in traditional distributed P2P network. The architecture is a multi-layer overlay network of peer units based on Super-P2P model. Clustering process is divided into two phases consisted...
In order to conquer the major challenges of current Web document clustering, i.e. huge volume of documents, high dimensional process, we proposed a simple agglomerative hierarchical k-means clustering (SAHKC) algorithm based on H-K (hierarchical k-means) algorithm, and a new model was used in this paper to describe the Web document, named as multiple feature vector space model (MFVSM). Experimental...
Modern organizations are geographically distributed. Using the traditional centralized association rule mining to discover useful patterns in such distributed system is not always feasible because merging data sets from different sites into a centralized site incurs huge network communication and time costs. This paper presents an efficient distributed association rule mining (ED-ARM) algorithm to...
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