|
|
|
|
LEADER |
00000nam a22000005i 4500 |
001 |
b3239618 |
003 |
MWH |
005 |
20191028003002.0 |
007 |
cr nn 008mamaa |
008 |
121227s1991 ne | s |||| 0|eng d |
020 |
|
|
|a 9789401135344
|
024 |
7 |
|
|a 10.1007/978-94-011-3534-4
|2 doi
|
035 |
|
|
|a (DE-He213)978-94-011-3534-4
|
050 |
|
4 |
|a E-Book
|
072 |
|
7 |
|a UYQ
|2 bicssc
|
072 |
|
7 |
|a COM004000
|2 bisacsh
|
072 |
|
7 |
|a UYQ
|2 thema
|
100 |
1 |
|
|a Pawlak, Z.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
|
245 |
1 |
0 |
|a Rough Sets
|h [electronic resource] :
|b Theoretical Aspects of Reasoning about Data /
|c by Z. Pawlak.
|
250 |
|
|
|a 1st ed. 1991.
|
264 |
|
1 |
|a Dordrecht :
|b Springer Netherlands :
|b Imprint: Springer,
|c 1991.
|
300 |
|
|
|a XVI, 231 p.
|b online resource.
|
336 |
|
|
|a text
|b txt
|2 rdacontent
|
337 |
|
|
|a computer
|b c
|2 rdamedia
|
338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
347 |
|
|
|a text file
|b PDF
|2 rda
|
490 |
1 |
|
|a Theory and Decision Library D:, System Theory, Knowledge Engineering and Problem Solving ;
|v 9
|
490 |
1 |
|
|a Springer eBook Collection
|
505 |
0 |
|
|a 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.
|
520 |
|
|
|a 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.
|
590 |
|
|
|a Loaded electronically.
|
590 |
|
|
|a Electronic access restricted to members of the Holy Cross Community.
|
650 |
|
0 |
|a Artificial intelligence.
|
650 |
|
0 |
|a Mathematical logic.
|
650 |
|
0 |
|a Operations research.
|
650 |
|
0 |
|a Decision making.
|
690 |
|
|
|a Electronic resources (E-books)
|
710 |
2 |
|
|a SpringerLink (Online service)
|
773 |
0 |
|
|t Springer eBooks
|
830 |
|
0 |
|a Theory and Decision Library D:, System Theory, Knowledge Engineering and Problem Solving ;
|v 9
|
830 |
|
0 |
|a Springer eBook Collection.
|
856 |
4 |
0 |
|u https://holycross.idm.oclc.org/login?auth=cas&url=https://doi.org/10.1007/978-94-011-3534-4
|3 Click to view e-book
|
907 |
|
|
|a .b32396181
|b 04-18-22
|c 02-26-20
|
998 |
|
|
|a he
|b 02-26-20
|c m
|d @
|e -
|f eng
|g ne
|h 0
|i 1
|
912 |
|
|
|a ZDB-2-SCS
|
912 |
|
|
|a ZDB-2-BAE
|
950 |
|
|
|a Computer Science (Springer-11645)
|
902 |
|
|
|a springer purchased ebooks
|
903 |
|
|
|a SEB-COLL
|
945 |
|
|
|f - -
|g 1
|h 0
|j - -
|k - -
|l he
|o -
|p $0.00
|q -
|r -
|s b
|t 38
|u 0
|v 0
|w 0
|x 0
|y .i21527830
|z 02-26-20
|
999 |
f |
f |
|i 13f37a07-6418-5450-a13e-e6c050a4abc7
|s 2275000e-1bd7-5cd4-bbd7-70451047398b
|
952 |
f |
f |
|p Online
|a College of the Holy Cross
|b Main Campus
|c E-Resources
|d Online
|e E-Book
|h Library of Congress classification
|i Elec File
|n 1
|