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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Uncertainty Management in Information Systems: From Needs to Solutions

Uncertainty Management in Information Systems: From Needs to Solutions

Motro, Amihai
Smets, Philippe

Hardcover

Business GeneralGeneral ComputersSystem Administration

ISBN10: 0792398033
ISBN13: 9780792398035
Publisher: Springer Nature
Published: Dec 31 1996
Pages: 464
Weight: 1.87
Height: 1.06 Width: 6.14 Depth: 9.21
Language: English
As its title suggests, Uncertainty Management in Information Systems is a book about how information systems can be made to manage information permeated with uncertainty. This subject is at the intersection of two areas of knowledge: information systems is an area that concentrates on the design of practical systems that can store and retrieve information; uncertainty modeling is an area in artificial intelligence concerned with accurate representation of uncertain information and with inference and decision-making under conditions infused with uncertainty. New applications of information systems require stronger capabilities in the area of uncertainty management. Our hope is that lasting interaction between these two areas would facilitate a new generation of information systems that will be capable of servicing these applications. Although there are researchers in information systems who have addressed themselves to issues of uncertainty, as well as researchers in uncertainty modeling who have considered the pragmatic demands and constraints of information systems, to a large extent there has been only limited interaction between these two areas. As the subtitle, From Needs to Solutions, indicates, this book presents view- points of information systems experts on the needs that challenge the uncer- tainty capabilities of present information systems, and it provides a forum to researchers in uncertainty modeling to describe models and systems that can address these needs.

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