The goal of this thesis is to extend the configuration model to arbitrarily sized clusters and furthermore to a graph after bond percolation. To achieve this we first explain the configuration model and the model for graphs with single edges and triangles. Where in the latter model we already see some results of the effect of clustering on the size of the giant component. This is then extended ...

The goal of this thesis is to extend the configuration model to arbitrarily sized clusters and furthermore to a graph after bond percolation. To achieve this we first explain the configuration model and the model for graphs with single edges and triangles. Where in the latter model we already see some results of the effect of clustering on the size of the giant component. This is then extended ...

The goal of this thesis is to extend the configuration model to arbitrarily sized clusters and furthermore to a graph after bond percolation. To achieve this we first explain the configuration model and the model for graphs with single edges and triangles. Where in the latter model we already see some results of the effect of clustering on the size of the giant component. This is then extended ...

Text mining is becoming vital as Web 2.0 offers collaborative content creation and sharing. Now Researchers have growing interest in text mining methods for discovering knowledge. Text mining researchers come from variety of areas like: Natural Language Processing, Computational Linguistic, Machine Learning, and Statistics. A typical text mining application involves preprocessing of text, stemm...

The goal of this thesis is to extend the configuration model to arbitrarily sized clusters and furthermore to a graph after bond percolation. To achieve this we first explain the configuration model and the model for graphs with single edges and triangles. Where in the latter model we already see some results of the effect of clustering on the size of the giant component. This is then extended ...

Data Analysis plays an important role for understanding different events. Cluster Analysis is widely used data mining technique for knowledge discovery. Clustering has wide applications in the field of Artificial Intelligence, Pattern Matching, Image Segmentation, Compression, etc. Clustering is the process of finding the group of objects such that objects in one group will be similar to one an...

Keyword search on data represented as graphs, is receiving lot of attention in recent years. Initial versions of keyword search systems assumed that the graph is memory resident. However, there are applications where the graph can be much larger than the available memory. This led to the development of search algorithms which search on a smaller memory resident summary graph (supernode graph), ...

Density peaks clustering (DPC) is a latest and well-known density-based clustering algorithm which offers advantages for finding clusters of arbitrary shapes compared to others algorithm. However, the attacker can deduce sensitive points from the known point when the cluster centers and sizes are exactly released in the cluster analysis. To the best of our knowledge, this is the first time that...