clustering quality
Axioms for Graph Clustering Quality Functions
... graph clustering quality functions consisting of six ...of quality functions, adaptive scale modularity, that satisfies all properties and has standard graph clustering quality ...
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CDV Index: A Validity Index for Better Clustering Quality Measurement
... From the above application domains, we are able to categorize these domain problems into two major parts: supervised learning and unsupervised learning. For supervised learning problems, there exists a given data set to ...
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Clustering Analysis of Collaborative Tagging Systems By Using The Graph Model
... for clustering quality ...a clustering scheme (in this case we used hierarchical clustering algorithm [11]) to two cases: i) before dimension reduction (depicted as a dotted blue line in ...
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Investigate the Performance of WordNet and Association Rules for Hard Clustering Web Document
... document clustering, there are only a few methods proposed to utilize the semantic relationships between words to improve the clustering quality ...document clustering algorithms based on the ...
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The Application of Clustering Technique to Water Quality of Surabaya River
... for Clustering Quality of Water Surabaya river” and working paper at Faculty of Mathematics and Natural Science, Universitas Negeri Semarang, 8 November ...
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AntHeaps: A New Hybrid Image Segmentation Algorithm using Ant Colonies
... the quality of classification with respect to time ...hierarchical clustering was used where ants acted with on heaps of pixels rather than individual ...better clustering quality and ...
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AN UNSUPERVISED ACTIVE CLASSIFICATION TECHIQUE FOR FACE RECOGNITION
... of clustering analysis is to select a suitable similarity measure to form clusters, and second is to evaluate the quality of the clusters ...the clustering quality of any partition of the data ...
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Document Clustering: How to Measure Quality of Clusters in Absence of Ground Truth
... any clustering algorithm is the value of the objective function that is set for the clustering ...the clustering algorithm is cross-validated against the known ...of clustering quality ...
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A Novel Cross Layer Based Energy Conservative and Spectrum Allocation Algorithm for WANETs
... agglomerative clustering in which the algorithm examines a chosen pair of clusters and makes a decision if they should or should not be ...agglomerative clustering in the form of a genetic algorithm ...more ...
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An Approach to Improve Quality of Document Clustering by Word Set Based Documenting Clustering Algorithm
... Document Clustering (WDC), and its competitors are evaluated in terms of accuracy, sensitivity to parameters, efficiency and ...the clustering quality measured by ...
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Hybrid Nearest Neighbors Ant Colony Optimization for Clustering Social Media Comments
... for clustering, especially when clustering the large ...the clustering using ACO can be done faster and more efficient without sacrificing the ...better clustering quality than k-means ...
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Inducing German Semantic Verb Classes from Purely Syntactic Subcategorisation Information
... the clustering (such as single-linkage: the output clusterings contain few very large and many singleton clusters) are hardly improved by k- ...hierarchical clustering meth- ods place k-Means in a local ...
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Side Information Gathering for Mining Text Data
... ABSTRACT: In many text mining applications, side-information is available along with the text documents. Such side- information may be of different kinds, such as document provenance information, the links in the ...
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Scalable Matching and Clustering of Entities with FAMER
... Entity resolution (ER) – also called deduplication, record linkage or object matching – is the task of identifying records that refer to the same real-world entity, such as specific costumers, products or publications. ...
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Sentence-Similarity Based Document Clustering Using Birch Algorithm
... hierarchical clustering algorithm that can be applied to any relational clustering problem, and its application to several non-sentence data sets has shown its performance to be comparable to k-means ...any ...
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Multimodel Document Summarization K-SVM Algorithm
... between clusters. However, the boundary points are easy to be misclassified in clustering. Inspired by this problem, our algorithm uses the clustering approach to select boundary points which are more ...
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Design and Develop Semantic Textual Document Clustering Model
... As text info area unit inherently unstructured, some researchers applied the different technique for document management. Researchers have presented the info discovery in writing system that uses the most effective ...
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A Novel Ensemble based Cluster Analysis using Similarity Matrices and Clustering Algorithm (SMCA)
... According to the suggested approach initially the data sets are selected from the sources to mine the results in the form of clusters. These data sets could be taken from the same data source or some heterogeneous ...
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Cultural commodity chains, cultural clusters, or cultural production chains?
... This work on the embedding of cultural production is not only confined to traditional social and economic categories, it is also concerned with local cultures of production, in particular issues about decisions on the ...
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Clustering Based Analytical Review for Improving the Quality of Primary Education in MP
... disclosure, and the second is protects data from contamination. There are number of MAC models have been introduced, few popular from that are-Bell -lapadula, jajodia [r] ...
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