Agents that reduce work and information overload
Communications of the ACM
Mediation in information systems
ACM Computing Surveys (CSUR)
Communications of the ACM
The sciences of the artificial (3rd ed.)
The sciences of the artificial (3rd ed.)
InfoSleuth: agent-based semantic integration of information in open and dynamic environments
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
The agent architecture of the University of Michigan digital library
Readings in agents
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Distributed Intelligent Agents
IEEE Expert: Intelligent Systems and Their Applications
Information Extraction: Techniques and Challenges
SCIE '97 International Summer School on Information Extraction: A Multidisciplinary Approach to an Emerging Information Technology
Gaz-Guide: Agent-Mediated Information Retrieval for Official Gazettes
PRIMA 2001 Proceedings of the 4th Pacific Rim International Workshop on Multi-Agents, Intelligent Agents: Specification, Modeling, and Applications
| Hi-index | 0.00 |
Much of information and knowledge are documented in free texts. Textual task capabilities and agencies are inevitably essential to successful information services. In this paper, we describe some empirical observations on information tasks in a context rich data domain and attempt to discuss its implications on agent system design. We have developed an agent system with two essential taskcapabilities - information retrieval and information extraction, which can be built upon for more value-added information services. We observed a number of textual information task characteristics, such as process-centric, independently decomposable operations, indispensable domain knowledge, and user driven task specification, that are influential to designing agent systems. We also propose a conceptual view on system design that considers three agent groups - task agent, knowledge agent, and operation agent. The characterization of agent roles helps determine primary functions needed and set apart stable intermediate forms in the system. Further analysis on relationship among components would reveal major types and patterns of interaction and how the agents should be designed to coordinate with each other.