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As an important preprocessing technology in patent knowledge utilization, patent classification should be accurate and efficient. Commonly used feature selection methods and classification algorithms, like information gain (IG) and k nearest neighbors (k-NN) algorithm, are superior in text classification but have some drawbacks in patent classification. In the paper, we focus on patent classification...
This paper proposed a new point symmetry-based ant clustering algorithm which can defect the number of clusters and the proper partitions from data sets when data sets possess the property of symmetry. In the proposed algorithm, a revised ant clustering algorithm is presented which can reduce the running time of standard ant clustering algorithm. Each ant represents a data object. It will decide its...
Clustering is a hot research field in data mining. There are so many methods or algorithms designed for different type data set on which data analysis action operates. Local Agglomerative Characteristic (LAC) based Algorithm, in this paper, is presented for data clustering, which can handle clusters of different size, shapes, and densities, can work well on different distributed and natural variant...
Case based reasoning (CBR) is very important task in data mining, but privacy information will be disclosed easily in CBR. This paper presents random locally linear embedding (LLE) on encrypted case based reasoning method. In order to be ensure the security of the CBR, the parameters nearest neighbor number k and embedded space dimension d of LLE algorithm are selected randomly. Further we embed the...
K-dominant skyline query has been proposed as an important operator for multi-criteria decision making, data mining and so on, this technology can reduce the large result sets of skyline query in high dimensional space. In this paper, a new concept was firstly proposed: k-dominant Skyline cube, which consists of all the k-dominant skylines. Although existing algorithms can compute every k-dominant...
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