Comparing and Unifying Search-Based and Similarity-Based Approaches to Semi-Supervised Clustering

Composite Kernel Optimization in Semi-Supervised Metric

Machine-learning solutions to classification, clustering and matching problems critically depend on the adopted metric, which in the past was selected heuristically. In the last decade, it has been demonstrated that an appropriate metric can be learnt from data, resulting in superior performance as compared with traditional metrics. This has recently stimulated a considerable interest in the to...

Wised Semi-Supervised Cluster Ensemble Selection: A New Framework for Selecting and Combing Multiple Partitions Based on Prior knowledge

The Wisdom of Crowds, an innovative theory described in social science, claims that the aggregate decisions made by a group will often be better than those of its individual members if the four fundamental criteria of this theory are satisfied. This theory used for in clustering problems. Previous researches showed that this theory can significantly increase the stability and performance of...

Submitted for publication Comparing and Unifying Sear h - Based and Similarity - BasedApproa hes to Semi - Supervised

Wised Semi-Supervised Cluster Ensemble Selection: A New Framework for Selecting and Combing Multiple Partitions Based on Prior knowledge

The Wisdom of Crowds, an innovative theory described in social science, claims that the aggregate decisions made by a group will often be better than those of its individual members if the four fundamental criteria of this theory are satisfied. This theory used for in clustering problems. Previous researches showed that this theory can significantly increase the stability and performance of...

A partition-based algorithm for clustering large-scale software systems

Clustering techniques are used to extract the structure of software for understanding, maintaining, and refactoring. In the literature, most of the proposed approaches for software clustering are divided into hierarchical algorithms and search-based techniques. In the former, clustering is a process of merging (splitting) similar (non-similar) clusters. These techniques suffered from the drawba...