Clustering is an unsupervised technique of Data Mining. It means grouping similar objects together and separating the dissimilar ones. Each object in the data set is assigned a class label in the clustering process using a distance measure. This paper has captured the problems that are faced in real when clustering algorithms are implemented .It also considers the most extensively used tools wh...

We introduce an analytical tool to study the convergence of bidirectional multiagent agreement systems and use it to sharpen the analysis of various natural algorithms, including flocking, opinion consensus, and synchronization systems. We also improve classic bounds about colored random walks and discuss the usefulness of algorithmic proofs.

In this paper, we use the so-called synthesis based modeling approach to synthesize a Petri net from specified behavior. At first, we model a set of single executions of a process by means of a very intuitive modeling language. In a second step, we use a synthesis algorithm to automatically produce a related Petri net model. Taking a look at the literature, compact regions define the state of t...

This report is to provide a tutorial and pointers to results and related work on timed automata with a focus on semantical and algorithmic aspects of verification tools. We present the concrete and abstract semantics of timed automata (based on transition rules, regions and zones), decision problems, and algorithms for verification. A detailed description on DBM (Difference Bound Matrices) is i...

We provide new tools, such as k-troikas and good subtreerepresentations, that allow us to give fast and simple algorithms computing branchwidth. We show that a graph G has branchwidth at most k if and only if it is a subgraph of a chordal graph in which every maximal clique has a k-troika respecting its minimal separators. Moreover, if G itself is chordal with clique tree T then such a chordal ...

this study proposes a modified version of cultural algorithms (cas) which benefits from rule-based system for influence function. this rule-based system selects and applies the suitable knowledge source according to the distribution of the solutions. this is important to use appropriate influence function to apply to a specific individual, regarding to its role in the search process. this rule ...

Parsing natural language is an essential step in several applications that involve document analysis, e.g. knowledge extraction, question answering, summarization, filtering. The best performing systems at the TREC Question Answering track employ parsing for analyzing sentences in order to identify the query focus, to extract relations and to disambiguate meanings of words. These are often dema...