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Use Commercial bots as Intelligent Agents

Commercial use of bots and intelligent agents.
Some examples of commercial applications of Web bots or intelligent agents include:
  1. Visual financial analysis agents: in data mining and analysis
  2. Infoagents: in information filtering and document management
  3. System management agents: as support system managers in monitoring and reporting important events
  4. Workflow agents: in call and email inquiry handling (this is used by a major international carrier, a leading photographic equipment manufacturer, and increasingly by smaller online businesses who answer Frequently Asked Questions in a chat room environment)

Intelligent agents in Knowledge Mining

The primary motivation for adopting intelligent agents in knowledge mining is to provide
  1. researcher,
  2. students and
  3. decision makers
with an insight of emerging techniques and their possible hybridization that can be used for dredging, capture, distributions and utilization of knowledge in the domain of interest e.g., business, engineering, and science. Knowledge mining using intelligent agents explores the concept of knowledge discovery processes and in turn enhances the decision making capability through the use of intelligent agents like ants, bird flocking, termites, honey bee, wasps, etc. This book blends two distinct disciplines, data mining and knowledge discovery process and intelligent agents based computing (swarm intelligence + computational Intelligence). In order to provide readers with an integrated set of concepts and techniques for understanding a rather recent yet pivotal task of knowledge discovery and also make them understand about their practical utility in intrusion detection, software engineering.
Several advances in computer science have been brought together under the title of knowledge discovery and data mining. Techniques range from simple pattern searching to advanced data visualization. Since our aim is to extract knowledge from various scientific domain using intelligent agents, our approach should be characterized as knowledge mining.