Clustering algorithm
Classification of Different Species Families using Clustering Algorithm
... [4]V. Guralnik, and G. Karypis, ”‘A scalable algorithm for clustering sequential data,” Proc. o/ Is‘ IEEE confer-ence on Data Mining, 2001. [5] An efficient incremental protein sequence clustering ...
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FctClus: A Fast Clustering Algorithm for Heterogeneous Information Networks.
... initial clustering. A high clustering quality is necessary for network analysis, but low computation speed is intolerable because of the large network scales ...LDCC algorithm[12] is improved, while ...
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Semantic Based Cluster Content Discovery in Description First Clustering Algorithm
... first clustering algorithm belong to the category in which the meaningful description is deduced first and then relevant documents are assigned to that ...Grouping Algorithm) is the algorithm ...
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A Novel K-Means Based Clustering Algorithm for High Dimensional Data Sets
... cluster algorithm separately to these subsets. The final clustering result is obtained by merging the previously formed ...conquer algorithm first divides the entire data set into r subsets with ...
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Clustering of User Behaviour based on Web Log data using Improved K-Means Clustering Algorithm
... step. Clustering was done twice in all three data sets algorithms with their proposed clustering algorithm, without selecting features and after selecting ...the clustering results are ...
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A Novel Density based improved k-means Clustering Algorithm – Dbkmeans
... Recently, clustering has been recognized as a primary data mining method for knowledge discovery in spatial ...the clustering algorithm employed, parameter settings used, and other ...Multiple ...
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Ant Colony Clustering Algorithm and Improved Markov Random Fusion Algorithm in Image Segmentation of Brain Images
... FCM clustering algorithm, and the search process is easy to fall into the local ...colony algorithm is proposed to combine with ...colony algorithm, the clustering center and the number ...
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A Novel Method to Predict Genomic Islands Based on Mean Shift Clustering Algorithm.
... Genomic Islands (GIs) are regions of bacterial genomes that are acquired from other organ- isms by the phenomenon of horizontal transfer. These regions are often responsible for many important acquired adaptations of the ...
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Extracting Attractive Local-Area Topics in Georeferenced Documents using a New Density-based Spatial Clustering Algorithm
... spatial clustering algorithm [7], ...spatial clustering algorithms must focus on high-density areas in data space, which are separated by areas of lower ...
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Evaluation of the Application of BIM Technology Based on PCA - Q Clustering Algorithm and Choquet Integral
... gray clustering algorithm to evaluate the risk index value, and finally quantitative analysis of PFI financing mode in the highway construction projects in the use of integrated ...
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A Modified Clustering Algorithm in WSN
... new algorithm proposed. LEACH is a clustering algorithm, which means the nodes of the network are organized within clusters and they communicate between themselves via sensor elements called Cluster ...
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Sybil Attack on Lowest Id Clustering Algorithm in The Mobile Ad Hoc Network
... this clustering scheme, as most of the clusters will be under the control of these Sybil attacker ...ID clustering algorithm in two different ...
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AN IMPROVED CLUSTERING ALGORITHM FOR CUSTOMER SEGMENTATION
... The algorithm starts with n number of clusters where n indicates the number of objects in the data ...this algorithm the output is consistent for the same data ...this algorithm the distance between ...
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Spatio-temporal data mining in palaeogeographic data with a density-based clustering algorithm
... Constraint-based clustering: Real-world applications may need to perform clustering under various kinds of ...good clustering behaviour that satisfy specified constraints [HAN & KAMBER, ...
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A Fast Clustering Algorithm for Mining Social Network Data
... Social news sites are an example of bipartite networks, where users and the news stories are the two types of nodes, and the positive votes given to stories are the links. Taking into account the literature, we prefer ...
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Incremental k-means clustering algorithms: a review
... Abstract: Clustering is the process of grouping the object based on their attributes and features such that the data objects that are similar or closer to each other are put in the same ...popular ...
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Automatic Clustering Approaches Based On Initial Seed Points
... partitional clustering algorithm the number of runs of clustering algorithm to converge to its objective function depends on the selection of initial seed ...of clustering depends on ...
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An Improved Collaborative Filtering Recommendation Algorithm Combining Item Clustering and Slope One Scheme
... widely-used algorithm in making rating prediction for recommendation ...recommendation algorithm combining item clustering method and weighted slope one ...our algorithm we use item ...
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ESTIMATING PROJECT DEVELOPMENT EFFORT USING CLUSTERED REGRESSION APPROACH
... based clustering method has been integrated with regression ...relational clustering algorithm uses grey relational analysis for weighting features and also for ...that clustering could ...
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An Efficient Way for Clustering Using Alternative Decision Tree
... results clustering algorithms, two of which most important is, clustering performance and meaningful cluster ...of clustering method is available, among those hierarchical clustering and ...
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