Improved Privacy

Data mining techniques have been widely used for extracting non-trivial information from massive amounts of data. They help in strategic decision-making as well as many more applications. However, data mining also has a few demerits apart from its usefulness. Sensitive information contained in the database may be brought out by the data mining tools. Different approaches are being utilized to hide the sensitive information. The proposed work in this article applies a novel method to access the generating transactions with minimum effort from the transactional database. It helps in reducing the time complexity of any hiding algorithm. The theoretical and empirical analysis of the algorithm shows that hiding of data using this proposed work performs association rule hiding quicker than other algorithms.

Using Semantic Web Concepts to Retrieve Specific Domain Information from the Web

Currently, systems dedicated to information retrieval/extraction perform an important role on fetching relevant and qualified information from the World Wide Web (WWW). The Semantic Web can be described as the Web’s future once it introduces a set of new concepts and tools. For instance, ontology is used to insert knowledge into contents of the current WWW to give meaning to such contents. This allows software agents to better understand the Web’s content meaning so that such agents can execute more complex and useful tasks to users. This work introduces an architecture that uses some Semantic Web concepts allied to Regular Expressions (REGEX) in order to develop a system that retrieves/extracts specific domain information from the Web. A prototype, based on such architecture, was developed to find information about offers announced on supermarkets Web sites.

Intelligent Agents for E-Learning

We propose the software architecture of a new generation of advisory systems using Intelligent Agent and Semantic Web technologies. Multi-agent systems provide a well-suited paradigm to implement negotiation processes in consultancy situations. Intelligent software agents act as clients and advisors using their knowledge in order to assist human users. In the proposed architecture the domain knowledge is semantically modeled by means of XML-based ontology languages such as OWL. Using an inference engine the agents reason on base of their knowledge to make decisions or proposals. The agent knowledge consists of different types of data: on the one hand private data, which has to be protected against unauthorized access, and on the other hand publicly accessible data spread over different web sites. Comparable to a real consultancy situation, an agent only reveals sensitive private data if it is indispensable for finding a solution. In addition, depending on the actual consultancy situation each agent dynamically expands its knowledge base by accessing OWL knowledge sources from the Internet. The usefulness of our approach is proved by the implementation of an advisory system whose objective is to develop virtual student advisers that render support to university students in order to successfully organize und perform their studies.

Combating Information Overload by Means of Information Customization Systems

The evolution of the Internet into the Global Information Infrastructure has led to an explosion in the amount of available information. The result is the “information overload” of the user, i.e., users have too much information to make a decision or remain informed about a topic. Information customization systems are supposed to be the answer for information overload. They allow users narrowcast what they are looking for and get information matching their needs. Information customization systems are also a bargain of consummate efficiency. The value proposition of such systems is reducing the time spent looking for information. We hold the view that information customization could be best done by combining various artificial intelligence technologies such as collaborative filtering, intelligent interfaces, agents, bots, web mining, and intermediaries. MASACAD, the system described in this chapter, is an example of an information customization system that combines many of the technologies already mentioned and others to approach information customization and combat information overload.

Using Semantic Technologies for the Support of Engineering Design Processes

The design and development processes of complex technical systems are of crucial importance to the competitiveness of a technology-oriented enterprise. These processes are characterised by high creativity and strong non deterministic dynamics. Established information science methods, however, are intended for more deterministic work processes. They cannot be effectively applied to support creative activities like conceptual synthesis, analysis, and decision-making. Therefore methods of experience management need to be exploited here. This paper presents a new integrated approach to such design process guidance based on capturing the process traces in a Process Data Warehouse (PDW). Both the products to be designed and the process steps corresponding, are structured and stored as extended method traces. This trace capture facilitates the processing and subsequent reuse of the information through a process-integrated development environment. The concept of the PDW has been evaluated in several engineering design case studies. One of those, which focuses on the conceptual design of a chemical production plant, will be described in more detail.

Integration of Management of Quality of Web Services in Service Oriented Architecture

With the proliferation of Web services and their wide adoption as a novel technology for business-to-business interactions on the Web, Quality of Web Services (QoWS) management has witnessed considerable interest in recent years. Most of the existing works regarding this issue do not provide support for the overall QoWS management operations and are very often limited to a subset of these operations. Some of these works propose QoWS solutions for only basic web services while others propose solutions for composite web services. In this chapter, we propose to extend the Service Oriented Architecture (SOA) with a framework for QoWS management in which services may be basic or composite Web services. The framework uses a layered approach to provide support for the most common QoWS management operations, which include QoWS specification, QoWS verification, QoWS negotiation, and QoWS monitoring. These operations are supported at both the design and the development phases of Web services.

A Service Discovery Model for Mobile Agent Based Distributed Data Mining

Mining information from distributed data sources over the Internet is a growing research area. The introduction of mobile agent paradigm opens a new door for distributed data mining and knowledge discovery applications. One of the main challenges of mobile agent technology is how to locate hosts that provide services requested by mobile agents. Traditional Service Location Protocols can be applied to mobile agent systems to explore the service discovery issue. However, because of their architecture deficiencies, they do not adequately solve all the problems that arise in a dynamic domain such as database location discovery. From this point of view, we need some enhanced service discovery techniques for the mobile agent community. This paper proposes a new model for solving the database service location problem in the domain of mobile agents by implementing a Service Discovery Module based on Search Engine techniques. As a typical interface provided by a mobile agent server, the Service Discovery Module improves the decision ability of mobile agents with respect to information retrieval. This research is part of the IMAGO system - an infrastructure for mobile agent based data mining applications. This paper focuses on the design of an independent search engine, IMAGOSearch and discusses how to integrate service discovery into the IMAGO system, thus providing a global scope service location tool for intelligent mobile agents.

Multiagent Systems and Web Services in Enterprise Environments

In this chapter we discuss the general aspects related to the utilization of MultiAgent systems in Enterprise environments with special emphasis on the integration architectures enabled by Web Service technologies. Also, we present a decoupled architectural approach that allows Software Agents to interoperate with enterprise systems using Web Services. The proposed solution leverages existing technologies and standards in order to reduce the time-to-market and increase the adoption of agent-based applications. Finally, we show some case studies of knowledge-oriented Web services that have been designed following the discussed approach and outline some current research and business concerns for the field.

Assisting Learners to Dynamically Adjust Learning Processes by Software Agents

In order to make online learning more productive, software agent technology has been applied to provide services for learners to assist them to construct knowledge in constructivist ways. This paper is focused on the application of software agents in assisting learners to dynamically adjust learning processes. Unlike pedagogical agents, the agents in this application do not hold domain knowledge but simply assist learners to get through the learning process by a variety of supportive services. They assist learners to develop personalized preferred learning plans and guide them to dynamically align learning towards their goals. In this paper, the online learning process is first investigated and an approach to assisting learners to dynamically adjust learning processes is outlined. Then the structure of the UOL (unit of learning) database that provides links between a practical learning scenario and the required services is explored. A multi-agent architecture for realizing the services is configured and the roles of the involved agents are described. After that, the related agent algorithms for guiding learners to dynamically adjust learning processes are described.

Implementing Seller Agent in Multiple Online Auctions

Online auctions are becoming extremely popular because of the convenience that it offers to the consumers. Much work has been done in designing bidding strategy that can be utilized by bidders who want to participate in online auctions. However, very little work has been done on the seller’s strategy for online auctions. In any online auction, the final selling price of the item is unknown until the auction closes. This price is dependent on several factors such as the number of bidders participating in the auction, how much each bidder is willing to pay for the product, how many online auctions are selling the same item as well as the duration of each auction. Each item to be auctioned off has a reserved price set by the seller. Setting the reserved price too high for the item will result in the item not being sold and setting the price too low may result in profit reduction or even loss. Deciding on the reserved price of an item to be auctioned off is not a straightforward decision. This paper reports on a preliminary implementation of a seller agent that recommends a reserved price for a given item to be auctioned off by the seller. The seller agent’s objective is to suggest a reservation price that guarantees the sale of the item within a given period (as required by the seller) with a profit.