[PDF] Top 20 K-Anonymity Through The Enhanced Clustering Method
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K-Anonymity Through The Enhanced Clustering Method
... this method can conceal information from unapproved get ...errands through bargaining information ...called k-obscurity has increased greater fame. In the k-obscurity technique, semi ... See full document
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An Enhanced Method for Randomized Dimensionality Reduction Using Roughset Based K-Means Clustering
... at clustering. It is distinguished by various type of clustering: Hierarchical (nested) versus partitioned (unnested), Exclusive versus overlapping versus fuzzy, complete versus ...of k-means ... See full document
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Enhanced Intrusion Network System using Fuzzy –K Mediod Clustering Method
... database through the machine a learning method that presents more than 90% accuracy, recall and ...based method with dataset KDD 1999 and KYOTO ...groups through k-mediod ...fuzzy ... See full document
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An Enhanced K Means Clustering Based on K SVD DWT Algorithm for Image Segmentation
... popularity. Clustering can be a method of organizing the items into teams supported its ...content-based clustering, content material implies to textures, shapes or the alternative data may be ... See full document
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GRAPH BASED TEXT REPRESENTATION FOR DOCUMENT CLUSTERING
... This method was one of the first techniques used for segmenting natural images due to its simplicity and efficiency ...a clustering method is depends on its ability to discover most of the hidden ... See full document
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Document Clustering Using Enhanced Tw-K-Means
... techniques used. This makes the user to choose one among the several available text mining techniques. In (Yannis Haralambous & Philippe Lenca, 2014), the authors use the concept of text item pruning and text ... See full document
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A data mining framework to analyze road accident data
... several clustering algorithms [14, 18] exist in the ...of clustering algorithm is to divide the data into different clusters or groups such that the objects within a group are similar to each other whereas ... See full document
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Enhanced Anonymization and Clustering of OSN Utkarsh K. Senthil Kumar
... During our work we found that using relative database was much more reliable as compared to absolute database. To address the second issue listed above; we need to estimate the performance of the best classifier that can ... See full document
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NORMALIZATION INDEXING BASED ENHANCED GROUPING K-MEAN ALGORITHM
... of K-Mean ...data. Clustering is an important technique of data mining. Clustering is that technique of data mining which divides the data into similar and dissimilar ...of k mean ... See full document
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Application of Capital Asset Pricing Model in Indian Stock Market
... problem. K- mean clustering is the most successful method of Recommender ...System. K- means clustering also K-Means ...Algorithm K-means (MacQueen, 1967) is one of the ... See full document
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K Anonymity Enhancement for Privacy Preservation with Hybridization of Cuckoo Search and Neural Network using Clustering
... authentication method on the basis of group signature for the authentication at trust levels than node identities for preventing the privacy leakage and for assuring the safe Pervasive Social Networking (PSN) ... See full document
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Current developments of k-anonymous data releasing
... the k-anonymity model by Samarati and ...on k-anonymisation provide simple and effective approaches to protect private in- formation of individuals via only releasing k-anonymous views of a ... See full document
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Achieving k-Anonymity by clustering in attribute hierarchical structures
... local-recoding method generalises attribute values at cell ...recoding method does not over- generalise a table and hence may minimise the distortion of an anonymous ...optimal k-anonymisation is ... See full document
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An Enhanced K-Means Clustering Algorithm to Remove Empty Clusters
... mining. Clustering is an important data analytic technique which has a significant role in data mining ...application. Clustering is the method of arranging a set of similar objects into a ...based ... See full document
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Enhanced K-Means Clustering Algorithm Using Collaborative Filtering Approach
... iterative method is use to cluster the ...then K-means will be the initial and final ...the K-means clustering algorithm, it attempt to cluster the data samples in dataset into preferred ... See full document
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(alpha, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing
... The k-anonymity model has been introduced for protecting individual ...(α, k)-anonymity model to protect both identifications and rela- tionships to sensitive information in ...(α, ... See full document
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Privacy preserving data sharing in data mining environment
... taking k- anonymity as an example [86, 103], it requires each record to be identical with at least k − 1 others with respect to a set of quasi-identifier ...integer k and a relational data set ... See full document
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AHAC: Decision Tree Classification with Agglomerative Hierarchical Algorithm Clustering for Time Series Data Clustering
... ABSTRACT: Clustering is the application of data mining techniques to discover patterns from the ...soft clustering concept, which is the process of deriving the information from the similarity from the ... See full document
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A Review on Privacy Violations of Data Anonymization
... (iii) Samurai’s Algorithm: it is binary search approach. It checks middle-level nodes of generalization hierarchy (IV) Optimal Lattice Anonymization (OLA) Algorithm: - This algorithm also starts from nodes at a h/2 level ... See full document
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Cluster Analysis of Electrical Behavior
... apply clustering analysis of data mining into power system. We adapt K-means clustering algorithm to analyze customer load, analyzing similar behavior between customer of electricity, and we adapt ... See full document
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