Mining Agents Research Articles

EMADS: An extendible multi-agent data miner

In this paper, we describe EMADS, an extendible multi-agent data mining system. The EMADS vision is that of a community of data mining agents, contributed by many individuals, interacting under decentralised control to address data mining requests. EMADS is seen both as an end user application and a research tool. This paper details the EMADS vision, the associated conceptual framework and the current implementation. Although EMADS may be applied to many data mining tasks; the study described here, for the sake of brevity, concentrates on agent based data classification. A full description of EMADS is presented.

A framework for discovering relevant patterns using aggregation and intelligent data mining agents in telematics systems

The emerging technology in vehicle telematics drives several stakeholders in this field to consider services that could be beneficial for both clients and the telematics service providers. In particular this paper proposes a novel framework for insurance telematics in Korea using a mobile aggregation agent (AA) and intelligent data mining agent (IDMA). To our knowledge, this model is recent of its kind in this country and the base-line information from driver’s characteristics serves as reference for the flexible insurance policies. We are able to present a use-case scenario and illustrative examples to demonstrate our model. With this flexible insurance framework, customers can manage their own insurance premiums and lower the cost of motoring. Promising applications of this system to business and industries have been recognized and discussed.

A data mining integrated architecture for shop floor control

The dynamics of the market are forcing shop floor control systems to enhance their intelligence and reactivity to change. The control system must also have mechanisms to process the vast amount of data, which is generated with the application of cheap data logging systems and should also incorporate a mechanism for continuous learning. Data mining provides a mechanism for analysing data and generating new knowledge. This paper presents an intelligent knowledge-based decision support system for shop floor control, which incorporates data mining techniques and intelligent agent technology to provide useful information, knowledge, and a mechanism for continuous learning. The functioning of the system is described and the architecture of different agents that constitute the system has been discussed in terms of the different modules required. A process to integrate the individual data mining agents associated with the different processes has also been described. Finally a prototype of the system is presented to demonstrate the application of this agent-based system.

Concepts, challenges, and prospects on Multiagent Data Warehousing (MADWH) and Multiagent Data Mining (MADM)

Multiagent Data Warehousing (MADWH) and Multiagent Data Mining (MADM) presents a multidimensional agent-oriented approach for brain modelling and decision making based on the hypothesis that a brain system consists of a society of semiautonomous neural agents and full autonomy is the result of coordination of semiautonomous functionalities. The agent-oriented approach leads to the following concepts, challenges, and prospects: agent laws, agentisation, agent discovery, law discovery, self-organisation, and reorganisation; mining agent association rules in 1st-order logic; modelling full autonomy as the result of coordination of semiautonomous agents; modelling evolving processes like growing and aging; modelling healthy states as well as unhealthy states of biological systems.

Organizing Multiple Data Sources for Developing Intelligent e-Business Portals

Enterprise applications usually involve huge, complex, and persistent data to work on, together with business rules and processes. In order to represent, integrate, and use the information coming from the huge, distributed, multiple sources, we present a conceptual model with dynamic multi-level workflows corresponding to a mining-grid centric multi-layer grid architecture, for multi-aspect analysis in building an e-business portal on the Wisdom Web. We show that this integrated model will help to dynamically organize status-based business processes that govern enterprise application integration. We also present two case studies to demonstrate the effectiveness of the proposed model in the real world. The first case study is about how to organize and mine multiple data sources for behavior-based online customer segmentation, which is the first crucial step of personalization and one-to-one marketing. The second case study is about how to evaluate and monitor data quality, which in return can optimize the knowledge discovery process for intelligent decision making. The proposed methodology attempts to orchestrate various mining agents on the mining-grid for integrating data and knowledge in a unified portal developed by a service-oriented architecture.

Bioinformatics and Bio-logics

Bioinformatics and Bio-logics Eugene Thacker Abstract Combining approaches from media studies and science studies, this essay explores the relationship between genetic and computer “codes” through a consideration of the burgeoning field of “bioinformatics”—the development and application of computer technologies to life science research. Bioinformatics ranges in its use from online genomic and proteomic databases to the use of software for gene discovery and protein folding analysis. It is linked to the software industry, governmental-corporate life science research, and application in “in silico biology,” medical genetic diagnostics, and database management. As a direct intersection of computer science and molecular biology, bioinformatics promises to transform the study of biological life into computation, where particular gene-protein interactions and even entire cells can be informatically understood through the use of computer technology. This essay provides a critical analysis of several bioinformatics systems, such as BLAST (a standard genome analysis tool). Focusing on the ways in which bioinformatics software contextualizes biological materiality, the essay argues that bioinformatics is a practice of “biomedia,” or the informatic recontextualization of biological components and processes. Bioinformatics thus privileges an informatic approach to the body, while evincing a deep investment in the ways in which biological materiality can be technically enhanced; the body becomes a technology, but a technology geared towards the production of a biotechnical body. Point-and-Click Biology It is often noted that progress in biotechnology research is as much a technological feat as a medical one. The field of “bioinformatics” is exemplary here, since it is playing a significant role in the various genome projects, the study of stem cells, gene targeting and drug development, medical diagnostics, and genetic medicine generally. Bioinformatics may simply be described as the application of computer science to molecular biology research. The development of biological databases (many of them online), gene sequencing computers, computer languages (such as XML-based standards), and a wide array of software tools (from pattern-matching algorithms to data mining agents), are all examples of innovations by means of which bioinformatics is transforming the traditional molecular biology laboratory. Some especially optimistic reports on these developments have suggested that the “wet” lab of traditional biology is being replaced by the “dry” lab of “point-and-click biology.” 1 Figure 1 Production Sequencing Facility at Department of Energy’s Joint Genome Institute in Walnut Creek, CA While current uses of bioinformatics are mostly pragmatic (technology-as-tool) and instrumental (forms of intellectual property and patenting), the issues which bioinformatics raises are simultaneously philosophical and technical. These issues have already begun to be explored in a growing body of critical work that approaches genetics and biotechnology from the perspective of language, textuality, and the various scripting tropes within molecular biology. The approach taken here, however, will be different. While critiques of molecular biology-as-text can effectively illustrate the ways in which bodies, texts, and contexts are always intertwined, I aim to interrogate the philosophical claims made by the techniques and technologies that molecular biotech designs for itself. Such an approach requires an inquiry into the materialist ontology that “informs” fields such as bioinformatics, managing as it does the relationships between the in vivo, the in vitro, and the in silico. Such questions have to do with how the intersection of genetic and computer codes is transforming the very definition of “the biological”—not only within bioinformatics but within molecular biotechnology as a whole. Thus, when we speak of the intersections of genetic and computer codes, we are not discussing the relationships between body and text, or material and semiotic registers, for this belies the complex ways in which “the body” has been enframed by genetics and biotechnology in recent years. What follows is a critical analysis of several types of bioinformatics systems, emphasizing how the technical details of software and programming are indissociable from these larger philosophical questions of biological “life.” The argument that will be made is that bioinformatics is much more than simply the “computerization” of genetics and molecular biology; it forms a set of practices that instantiate ontological claims about the ways in which the relationships between materiality and data, genetic and computer codes, are being transformed through biotech research. Bioinformatics in...

Mining stock price using fuzzy rough set system

Abstract In this study of mining stock price data, we attempt to predict the stronger rules of stock prices. To address this problem, we proposed an effective method, a fuzzy rough set system to predict a stock price at any given time. Our system has two agents: one is a visual display agent that helps stock dealers monitor the current price of a stock and the other is a mining agent that helps stock dealers make decisions about when to buy or sell stocks. To demonstrate that our system is effective, we used it to predict the stronger rules of stock price and achieved at least 93% accuracy after 180 trials.

Complementing search engines with online web mining agents

While search engines have become the major decision support tools for the Internet, there is a growing disparity between the image of the World Wide Web stored in search engine repositories and the actual dynamic, distributed nature of Web data. We propose to attack this problem using an adaptive population of intelligent agents mining the Web online at query time. We discuss the benefits and shortcomings of using dynamic search strategies versus the traditional static methods in which search and retrieval are disjoint. This paper presents a public Web intelligence tool called MySpiders, a threaded multiagent system designed for information discovery. The performance of the system is evaluated by comparing its effectiveness in locating recent, relevant documents with that of search engines. We present results suggesting that augmenting search engines with adaptive populations of intelligent search agents can lead to a significant competitive advantage. We also discuss some of the challenges of evaluating such a system on current Web data, introduce three novel metrics for this purpose, and outline some of the lessons learned in the process.

Intelligent agent-assisted decision support systems: Integration of knowledge discovery, knowledge analysis, and group decision support

The integration of data mining techniques with decision support systems to assist in dealing with information overload has received increased attention and importance over recent years. However, challenges remain regarding practical deployment and implementation of such integration, due to the increased complexity of decision making, system co-ordination and knowledge communication. It is the purpose of this paper to outline the issues necessary to be addressed in a practical decision support system that integrates data mining techniques. The paper will describe a novel architecture to support the co-operative decision process by utilizing event-driven and task-driven data mining agents, along with user assistant agents and a knowledge manager agent. An internet-based prototype for supporting marketing planning decisions is also presented to demonstrate the practicality and feasibility of the proposed intelligent agent-based decision support system architecture.

Lost & Found: 55. Francis Downing (1777-1857) and Mrs. Downing

It has already been recorded in the LF columns that Mrs. Downing provided fossil material figured by Murchison, whilst it was her husband *My kind friend Mr Downing of the Priory [Dudley], to whom I am above all other persons indebted for an acquaintance with the structure of the Dudley district* (p.485) whose job as a mining agent gave him a working knowledge of the geology of Dudley. Further figured specimens may be at Birmingham University Museum as the collection of William Mathews (1828-1901) housed there contains original Downing material (GCG, 2(6), 352) (see Fig.2)....

Lost & Found: 55. Downing, Francis and Mrs. (fl. 1796-1843)

Mrs, Downing who transmitted the type of fig. 4 is the wife of Murchison's subscriber Francis Downing Esq. of the Priory, DUDLEY, Staffs, whose help Murchison acknowledges on pp. xxix, 470, 475, 485, 490, 492, 653. Francis Downing was a mine agent of Dudley who from 1822-1843 was a member of the Dudley Canal Committee (see C. Hadfield 1966 The Canals of the West Midlands p. 109). Such activities explain an active interest in geology. Downing was a member of a notable Dudley landowning family and was mining agent to Lord Dudley from 1796 to 1836 when he was dismissed by Lord Dudley. (see V. L. Davies...