Theory and decision library., Series D,, System theory, knowledge engineering, and problem solving ;, 9.
یادداشتهای مربوط به مندرجات
متن يادداشت
I. Theoretical Foundations --; 1. Knowledge --; 2. Imprecise Categories, Approximations and Rough Sets --; 3. Reduction of Knowledge --; 4. Dependencies in Knowledge Base --; 5. Knowledge Representation --; 6. Decision Tables --; 7. Reasoning about Knowledge --; II. Applications --; 8. Decision Making --; 9. Data Analysis --; 10. Dissimilarity Analysis --; 11. Switching Circuits --; 12. Machine Learning.
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
To-date computers are supposed to store and exploit knowledge. At least that is one of the aims of research fields such as Artificial Intelligence and Information Systems. However, the problem is to understand what knowledge means, to find ways of representing knowledge, and to specify automated machineries that can extract useful information from stored knowledge. Knowledge is something people have in their mind, and which they can express through natural language. Knowl edge is acquired not only from books, but also from observations made during experiments; in other words, from data. Changing data into knowledge is not a straightforward task. A set of data is generally disorganized, contains useless details, although it can be incomplete. Knowledge is just the opposite: organized (e.g. laying bare dependencies, or classifications), but expressed by means of a poorer language, i.e. pervaded by imprecision or even vagueness, and assuming a level of granularity. One may say that knowledge is summarized and organized data - at least the kind of knowledge that computers can store.
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Artificial intelligence.
موضوع مستند نشده
Computer science.
موضوع مستند نشده
Logic, Symbolic and mathematical.
رده بندی کنگره
شماره رده
Q335
نشانه اثر
.
B993
1991
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )