Gurpreet Singh Bhamra

Intelligent Software Agent Technology: An Overview

Mobile Agent is an autonomously transportable code migrating itself from one node to another in a heterogeneous network without losing its operability. They have become commercially practicable with recent technologies and have the potential for revolutionizing distributed and network applications more recently in wireless sensor networks and bioinformatics. The main aim of this study is to motivate the researchers into the field of intelligent software agent technology by providing an overview and updated comparison of the current mobile agent platforms. General Terms Distributed Computing, Agent Technology.

Agent enriched distributed association rules mining: a review

Distributed Data Mining (DDM) is concerned with application of the classical Data Mining (DM) approach in a Distributed Computing (DC) environments so that the available resource including communication networks, computing units and distributed data repositories, human factors etc. can be utilized in a better way and on-line, real-time decision support based distributed applications can be designed. A Mobile Agent (MA) is an autonomous transportable program that can migrate under its own or host control from one node to another in a heterogeneous network. This paper highlights the agent based approach for mining the association rules from the distributed data sources and proposed an another framework called Agent enriched Mining of Strong Association Rules (AeMSAR) from Distributed Data Sources. As agent technology paradigm of the DC has gained lots of research in the recent years, therefore, making an alliance of agent and Association Rules Mining(ARM) will help mining the Association rules in a Distributed environment in a better way.

An encounter with Strong Association Rules

Data Mining (DM) is the process of automated extraction of interesting data patterns representing knowledge, from the large data sets. Frequent itemsets are the itemsets that appear in a data set frequently. Finding such frequent itemsets plays an essential role in mining associations, correlations, and many other interesting relationships among itemsets in transactional database. In this paper an algorithm, SAR (Strong Association Rule), is designed and implemented to check whether an Association Rule (AR) is strong enough or not. Apriori algorithm is also implemented to generate Frequent k-itemsets. A Binary Transactional Dataset is used for implementing the algorithm in java language.

AGENT ENABLED MINING OF DISTRIBUTED PROTEIN DATA BANKS

Mining biological data is an emergent area at the intersection between bioinformatics and data mining (DM). The intelligent agent based model is a popular approach in constructing Distributed Data Mining (DDM) systems to address scalable mining over large scale distributed data. The nature of associations between different amino acids in proteins has also been a subject of great anxiety. There is a strong need to develop new models and exploit and analyze the available distributed biological data sources. In this study, we have designed and implemented a multi-agent system (MAS) called Agent enriched Quantitative Association Rules Mining for Amino Acids in distributed Protein Data Banks (AeQARM-AAPDB). Such globally strong association rules enhance understanding of protein composition and are desirable for synthesis of artificial proteins. A real protein data bank is used to validate the system.

An Investigation into the Central Data Warehouse based Association Rule Mining

Data Mining(DM) technique is used to mine interesting hidden knowledge from large databases using various computational techniques/tools. Association Rule Mining(ARM) today is one of the most important aspects of DM tasks. In ARM all the strong association rules are generated from the Frequent Itemsets. In this study a central Data Warehouse based client-server model for ARM is designed, implemented and tested. The Outcome of this investigation and the advantages of software agents forms the base and motivation of using software agent technology in Distributed Data Mining.

Protein Databank Filtering and Amino Acid Frequency Calculator (PFA2FC): A Tool

Data Mining is the process of automatic extraction of useful patterns in the form of knowledge from the huge databases. Bioinformatics or computational molecular biology deals with the design and use of computer software to solve the complex biological problem. Proteins are important constituents of cellular machinery of any living organism and the functioning of proteins heavily depends upon its amino acids. A tool called Protein databank Filtering and Amino Acid Frequency Calculator (PFA2FC) has been designed using Java language to mine the Protein databank and find the frequencies of each amino acid within a protein.