[PDF] Top 20 A Microblock Density-Based Similarity Measure for Graph Clustering
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A Microblock Density-Based Similarity Measure for Graph Clustering
... The Zachary’s network is the members’ relationships of a karate club in the United States, which is a well-known test benchmark in community detection. As Fig. 7(a) shows, the club consists of 34 vertices, each vertex ... See full document
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Comparison of chemical clustering methods using graph- and fingerprint-based similarity measures
... of similarity between a pair of molecules but the NP-complete nature of the maximum common subgraph isomorphism problem has ruled out the large-scale use of MCS-based ...permit graph-based ... See full document
25
Clustering Multi Attribute Uncertain Data using Probability Distribution
... objects. Clustering uncertain data is one of the essential tasks in mining uncertain ...for clustering uncertain data based on probability distribution, uses Kullback-Leibler divergence to ... See full document
5
AHAC: Decision Tree Classification with Agglomerative Hierarchical Algorithm Clustering for Time Series Data Clustering
... for clustering of time series based on their structural ...clusters based on global features extracted from the time ...a measure to assess their similarity is a core part of many ... See full document
5
A Graph-based Text Similarity Measure That Employs Named Entity Information
... text-similarity measure, which employs named-entities’ informa- tion extracted from the texts and the n- gram graphs’ model for representing doc- ...text similarity mea- sure is embedded in a text ... See full document
7
Document Clustering based on Topic Maps
... document clustering based on topic maps representation of the ...the similarity measure between a pair of documents. This measure is used to cluster the set of documents by using ... See full document
5
Nearest-Neighbour-Induced Isolation Similarity and Its Impact on Density-Based Clustering
... dependent similarity called Isola- tion Kernel/Similarity has enabled SVM to produce better classification ...Isolation Similarity; and propose a nearest neighbour method ...Isolation ... See full document
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Fast and Accurate Spectral Clustering Based KNN Similarity Graph Analysis
... results based on a radial similarity function with sufficiently fast tail ...high density area of a particular component, which is at the tails of other components, the eigenvectors from all other ... See full document
7
A New Structural Similarity Measure: Clustering of Multi-Structured Documents
... is based on a measure of structural similarity that we have ...A measure based on matching graphs. It is based on a weighting function that reflects the hierarchical and ... See full document
9
Kailing, Karin (2004): New Techniques for Clustering Complex Objects. Dissertation, LMU München: Fakultät für Mathematik, Informatik und Statistik
... a graph as feature vector and the Manhattan distance between the feature vectors as similar- ity ...their measure can be calculated efficiently, it is not applicable to attributed ...a measure ... See full document
229
SSM DENCLUE : Enhanced Approach for Clustering of Sequential Data: Experiments and Test Cases
... personalization. Clustering web sessions is to group them based on similarity and consists of minimizing the Intra-cluster similarity and maximizing the Inter-group ...to measure ... See full document
7
Efficient Density Based Clustering Method for Two Dimensional Data
... patterns. Clustering and classification are amongst the most popular data mining ...of clustering algorithms, because of their significant role in allowing automatic identification of unlabeled records by ... See full document
7
An Emphasizing Approach based on Enhanced Intuitionistic Fuzzy Logic Segmentation on Objects in Video Sequences
... background, based on motion ...step based on spatio-temporal information. An object-based representation of video shots is composed by a background still image and moving ...is based on ... See full document
5
Clustering Optimal Algorithm- A Survey
... the clustering and finding the best cluster is difficult ...a clustering algorithm which fits with consensus ...Consensus clustering is the process of finding the best clustering from multiple ... See full document
7
An Efficient Fuzzy Data Clustering Algorithm for Relational Databases
... cluster based on some similarity measure ...new measure for calculation of similarity between two clusters for categorical attributes in a relational database ...inter ... See full document
8
A Novel Similarity Measure For Frequent Term Based Text Clustering On High Dimensional Data
... Text clustering plays an important role in information retrieval, topic tracking and detection, web information mining and other ...text clustering, texts with similar characteristics are in the aggregate ... See full document
5
Functional models and extending strategies for ecological networks
... raw-distance graph corresponding to sites where the target species has been reported to be found, and link node pairs with an edge if their distance is below the ...the graph on the full node set from the ... See full document
15
Document Similarity Measure for Classification and Clustering using TF-IDF
... Cosine similarity [4] is a measure taking the cosine of the angle between two ...Bray-Curtis similarity measure is a city-block metric which is sensitive to outlying ...the similarity ... See full document
5
Feature Values Analysis for Similarity Measure to Text Classification and Clustering
... The feature value can be term frequency (the number of occurrences of a term appearing in the document), relative term frequency (the ratio between the term frequency and the total number of occurrences of all the terms ... See full document
6
Document Classification and Clustering using Feature Extraction for Similarity Measure
... of clustering and retrieval of text data, system provides a fine classification of data ...hierarchical clustering in this system gives high level accuracy and classification of ...document ... See full document
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