Can Many Agents Answer Questions Better than One? 
The paper addresses the issue of how online natural language question answering, based on deep semantic analysis, may compete with currently popular keyword search, open domain information retrieval systems, covering a horizontal domain. We suggest the multiagent question answering approach, where each domain is represented by an agent which tries to answer questions taking into account its specific knowledge. The meta–agent controls the cooperation between question answering agents and chooses the most relevant answer(s). We argue that multiagent question answering is optimal in terms of access to business and financial knowledge, flexibility in query phrasing, and efficiency and usability of advice. The knowledge and advice encoded in the system are initially prepared by domain experts. We analyze the commercial application of multiagent question answering and the robustness of the meta–agent. The paper suggests that a multiagent architecture is optimal when a real world question answering domain combines a number of vertical ones to form a horizontal domain.
Galitsky, Boris and Rajesh Pampapathi. First Monday (2005). Articles>Language>Information Design>Semantic
The Linguistic Foundation of Labeling
A discussion of why to employ principle-based information architecture.
Warner, Amy J. ASIST (2004). Articles>Language>Information Design
Synonym Rings and Authority Files
In part 3 of the continuing series on controlled vocabularies and faceted classification, the authors explain synonym rings and authority files and how their use can bridge the gap between natural language and complex controlled vocabularies (taxonomies and thesauri).
Fast, Karl, Fred Leise and Mike Steckel. Boxes and Arrows (2003). Articles>Information Design>Indexing>Language
A tutorial on the basics of constructing an information retrieval thesaurus. It includes a glossary of thesaurus terms.
Craven, Timothy C. University of Western Ontario (1998). Articles>Language>Information Design>Metadata
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