Pattern Detection and Discovery (Record no. 187714)
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001 - CONTROL NUMBER | |
control field | 978-3-540-45728-2 |
003 - CONTROL NUMBER IDENTIFIER | |
control field | DE-He213 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20240423132431.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
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fixed length control field | 121227s2002 gw | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9783540457282 |
-- | 978-3-540-45728-2 |
024 7# - OTHER STANDARD IDENTIFIER | |
Standard number or code | 10.1007/3-540-45728-3 |
Source of number or code | doi |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
Classification number | QA76.9.D3 |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | UN |
Source | bicssc |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | COM021000 |
Source | bisacsh |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | UN |
Source | thema |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 005.74 |
Edition number | 23 |
245 10 - TITLE STATEMENT | |
Title | Pattern Detection and Discovery |
Medium | [electronic resource] : |
Remainder of title | ESF Exploratory Workshop, London, UK, September 16-19, 2002. / |
Statement of responsibility, etc | edited by David J Hand, Niall, M. Adams, Richard J. Bolton. |
250 ## - EDITION STATEMENT | |
Edition statement | 1st ed. 2002. |
264 #1 - | |
-- | Berlin, Heidelberg : |
-- | Springer Berlin Heidelberg : |
-- | Imprint: Springer, |
-- | 2002. |
300 ## - PHYSICAL DESCRIPTION | |
Extent | XII, 232 p. |
Other physical details | online resource. |
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-- | computer |
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-- | rdamedia |
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-- | online resource |
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-- | text file |
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-- | rda |
490 1# - SERIES STATEMENT | |
Series statement | Lecture Notes in Artificial Intelligence, |
International Standard Serial Number | 2945-9141 ; |
Volume number/sequential designation | 2447 |
505 0# - FORMATTED CONTENTS NOTE | |
Formatted contents note | General Issues -- Pattern Detection and Discovery -- Detecting Interesting Instances -- Complex Data: Mining Using Patterns -- Determining Hit Rate in Pattern Search -- An Unsupervised Algorithm for Segmenting Categorical Timeseries into Episodes -- If You Can’t See the Pattern, Is It There? -- Association Rules -- Dataset Filtering Techniques in Constraint-Based Frequent Pattern Mining -- Concise Representations of Association Rules -- Constraint-Based Discovery and Inductive Queries: Application to Association Rule Mining -- Relational Association Rules: Getting Warmer -- Text and Web Mining -- Mining Text Data: Special Features and Patterns -- Modelling and Incorporating Background Knowledge in theWeb Mining Process -- Modeling Information in Textual Data Combining Labeled and Unlabeled Data -- Discovery of Frequent Word Sequences in Text -- Applications -- Pattern Detection and Discovery: The Case of Music Data Mining -- Discovery of Core Episodes from Sequences -- Patterns of Dependencies in Dynamic Multivariate Data. |
520 ## - SUMMARY, ETC. | |
Summary, etc | The collation of large electronic databases of scienti?c and commercial infor- tion has led to a dramatic growth of interest in methods for discovering struc- res in such databases. These methods often go under the general name of data mining. One important subdiscipline within data mining is concerned with the identi?cation and detection of anomalous, interesting, unusual, or valuable - cords or groups of records, which we call patterns. Familiar examples are the detection of fraud in credit-card transactions, of particular coincident purchases in supermarket transactions, of important nucleotide sequences in gene sequence analysis, and of characteristic traces in EEG records. Tools for the detection of such patterns have been developed within the data mining community, but also within other research communities, typically without an awareness that the - sic problem was common to many disciplines. This is not unreasonable: each of these disciplines has a large literature of its own, and a literature which is growing rapidly. Keeping up with any one of these is di?cult enough, let alone keeping up with others as well, which may in any case be couched in an - familiar technical language. But, of course, this means that opportunities are being lost, discoveries relating to the common problem made in one area are not transferred to the other area, and breakthroughs and problem solutions are being rediscovered, or not discovered for a long time, meaning that e?ort is being wasted and opportunities may be lost. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Database management. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Artificial intelligence. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Algorithms. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Data structures (Computer science). |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Information theory. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Computer science |
General subdivision | Mathematics. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Mathematical statistics. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Information storage and retrieval systems. |
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Database Management. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Artificial Intelligence. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Algorithms. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Data Structures and Information Theory. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Probability and Statistics in Computer Science. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Information Storage and Retrieval. |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Hand, David J. |
Relator term | editor. |
Relator code | edt |
-- | http://id.loc.gov/vocabulary/relators/edt |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Adams, Niall, M. |
Relator term | editor. |
Relator code | edt |
-- | http://id.loc.gov/vocabulary/relators/edt |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Bolton, Richard J. |
Relator term | editor. |
Relator code | edt |
-- | http://id.loc.gov/vocabulary/relators/edt |
710 2# - ADDED ENTRY--CORPORATE NAME | |
Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY | |
Title | Springer Nature eBook |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Printed edition: |
International Standard Book Number | 9783540441489 |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Printed edition: |
International Standard Book Number | 9783662199459 |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
Uniform title | Lecture Notes in Artificial Intelligence, |
-- | 2945-9141 ; |
Volume number/sequential designation | 2447 |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | <a href="https://doi.org/10.1007/3-540-45728-3">https://doi.org/10.1007/3-540-45728-3</a> |
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942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks-CSE-Springer |
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