By Amihai Motro, Igor Rakov (auth.), Troels Andreasen, Henning Christiansen, Henrik Legind Larsen (eds.)
Flexible question Answering Systems is an edited number of contributed chapters. It makes a speciality of constructing computers in a position to remodeling a question into a solution with necessary info. The emphasis is on difficulties linked to high-level clever answering structures.
The assurance is multidisciplinary with chapters via authors from details technology, common sense, fuzzy structures, databases, man made intelligence and data illustration. each one contribution represents a conception related to flexibility in query-answering, and every addresses particular answering difficulties. insurance contains issues similar to fuzzy units in versatile querying, non-standard database interactions, metareasoning and brokers, etc.
Contributions for this quantity have been written by means of best researchers from their respective topic components, together with Patrick Bosc, Bernadette Bouchon-Meunier, Amihai Motro, Henri Prade and Ron Yager, between others.
Flexible question Answering Systems is a well timed contribution for researchers engaged on high-level question mechanism systems.
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Extra info for Flexible Query Answering Systems
Sample text
The notation All. Weight, refer to the weight of the current object in the table All. The fuzzy relation similar to ~w is defined in Fig. a where the membership degree of the two arguments x and Weight is 1 for x = Weight and 0 when the distance between x and Weight is greater than 10 Kg. We assume triangular form. 38 FLEXIBLE QUERY ANSWERING SYSTEMS p ... -_40-_ Weight -610 x a. 0 70 i 75 ,',' ,I~III, I 80 85 b. 8 a. The definition of the fuzzy concept similar to (:::::i w ) for the weight and h.
International Journal of Intelligent Systems, 11(10):717-732, October 1996. [Motro, Smets, 1996] A. Motro and Ph. Smets, editors. Uncertainty Management in Information Systems: From Needs to Solutions. Kluwer Academic Publishers, 1996. [Motro, Rakov, 1996] A. Motro and I. Rakov. On the specification, measurement, and inference of the quality of data. Technical report, Dept. Information and Software Systems Engineering, George Mason University, 1996. [Olken, Rotem, 1995] F. Oiken and D. Rotem. Random sampling from databases - a survey.
Because of the cost of establishing goodness estimations, we have noted that our methods are most suitable for static information. When the information is dynamic, it would be advisable to timestamp the estimations at the time that they were obtained and attach these timestamps to all quality inferences. One may also consider the automatic attenuation of quality estimations as time progresses. This direction is still outside our immediate objectives. References [Bort, 1995] J. Bort. Scrubbing dirty data.