Showing 517–528 of 2014 results
Cluster ensemble selection based on relative validity indexes Abstract?Cluster ensemble selection based on relative validity indexes. Selective clustering ensemble is usually based on the reference partition to select members of the ensemble. General method of generating reference partition is to use preliminary ensemble results, < Final Year Projects > yet it cannot eliminate the influence…
Cluster ensemble selection based on relative validity indexes Abstract?There are variety of methods available to solve multi-objective optimization problems, very few utilizes criterion linkage between data objects in the searching phase, to improve final result. This article proposes an evolutionary clustering algorithm for multi-objective optimization. This paper aims to identify more relevant features based on…
Clustering Based Discriminant Analysis for Eye Detection Abstract?Clustering Based Discriminant Analysis for Eye Detection. This paper proposes three clustering-based discriminant analysis (CDA) models to address the problem that the Fisher linear discriminant may not be able to extract adequate features for satisfactory performance, especially for two class problems. The first CDA model, CDA-1, divides…
Clustering Deviations for Black Box Regression Testing of Database Applications Abstract? Clustering Deviations for Black Box Regression Testing of Database Applications.Regression tests often result in many deviations < Final Year Projects 2016 > differences between two system versions, either due to changes or regression faults. For the tester to analyze such deviations efficiently, it would…
Clustering Sentence-Level Text Using a Novel Fuzzy Relational Clustering Algorithm Abstract?Clustering Sentence-Level Text Using a Novel Fuzzy Relational Clustering Algorithm. In comparison with hard clustering methods, in which a pattern belongs to a single cluster, fuzzy clustering algorithms allow patterns to belong to all clusters with differing degrees of membership. This is important in domains…
Clustering Sentence-Level Text Using a Novel Fuzzy Relational Clustering Algorithm Abstract?Clustering Sentence-Level Text Using a Novel Fuzzy Relational Clustering Algorithm. In comparison with hard clustering methods, in which a pattern belongs to a single cluster, fuzzy clustering algorithms allow patterns to belong to all clusters with differing degrees of membership. This is important in domains…
Co-ClusterD: A Distributed Framework for Data Co-Clustering with Sequential Updates Abstract?Co-clustering has emerged to be a powerful data mining tool for two-dimensional co-occurrence and dyadic data. However, co-clustering algorithms often require significant computational resources and have been dismissed as impractical for large data sets. Existing studies have provided strong empirical evidence that expectation-maximization < Final…
Co-Extracting Opinion Targets and Opinion Words from Online Reviews Based on the Word Alignment Model Abstract? Co-Extracting Opinion Targets and Opinion Words from Online Reviews Based on the Word Alignment Model. Mining opinion targets and opinion words from online reviews are important tasks for ?ne-grained < Final Year Projects 2016 > opinion mining, the key…
Co-Occurrence based Diffusion for expert search on the web Abstract? Expert search has been studied in different contexts, e.g., enterprises, academic communities. We examine a general expert search problem: searching experts on the web, where millions of webpages and thousands of names are considered. It has mainly two challenging issues: 1) webpages could be…
Coalescing Clustering and Classi?cation Abstract?Coalescing Clustering and Classi?cation. In Data Mining Clustering and Classification are two important techniques. In this paper we make use of large database (Diabetes dataset containing) to perform an integration of clustering and classification technique. We compared the results of simple classification technique (J48 classifier) with the results of integration of…
CoCoWa: A Collaborative Contact-Based Watchdog for Detecting Selfish Nodes Abstract? CoCoWa: A Collaborative Contact-Based Watchdog for Detecting Selfish Nodes. Mobile ad-hoc networks < Final Year Projects 2016 > MANETs assume that mobile nodes voluntary cooperate in order to work properly. This cooperation is a cost-intensive activity and some nodes can refuse to cooperate, leading to…
CoCoWa: A Collaborative Contact-Based Watchdog for Detecting Selfish Nodes Abstract? Mobile ad-hoc networks (MANETs) assume that mobile nodes voluntary cooperate in order to work properly. This cooperation is a cost-intensive activity and some nodes can refuse to cooperate, leading to a selfish node behavior. Thus, the overall network performance could be seriously affected. The use…
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