Data Mining and Knowledge Discovery for Big Data (Record no. 93456)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 03422nam a22004455i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-642-40837-3 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20140220082521.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 130924s2014 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783642408373 |
| -- | 978-3-642-40837-3 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-3-642-40837-3 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | Q342 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYQ |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | COM004000 |
| Source | bisacsh |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.3 |
| Edition number | 23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Chu, Wesley W. |
| Relator term | editor. |
| 245 10 - TITLE STATEMENT | |
| Title | Data Mining and Knowledge Discovery for Big Data |
| Medium | [electronic resource] : |
| Remainder of title | Methodologies, Challenge and Opportunities / |
| Statement of responsibility, etc | edited by Wesley W. Chu. |
| 264 #1 - | |
| -- | Berlin, Heidelberg : |
| -- | Springer Berlin Heidelberg : |
| -- | Imprint: Springer, |
| -- | 2014. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | X, 311 p. 99 illus., 29 illus. in color. |
| Other physical details | online resource. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 490 1# - SERIES STATEMENT | |
| Series statement | Studies in Big Data, |
| International Standard Serial Number | 2197-6503 ; |
| Volume number/sequential designation | 1 |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Aspect and Entity Extraction for Opinion Mining -- Mining Periodicity from Dynamic and Incomplete Spatiotemporal Data -- Spatio-Temporal Data Mining for Climate Data: Advances, Challenges -- Mining Discriminative Subgraph Patterns from Structural Data -- Path Knowledge Discovery: Multilevel Text Mining as a Methodology for Phenomics -- InfoSearch: A Social Search Engine -- Social Media in Disaster Relief: Usage Patterns, Data Mining Tools, and Current Research Directions -- A Generalized Approach for Social Network Integration and Analysis with Privacy Preservation -- A Clustering Approach to Constrained Binary Matrix Factorization. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | The field of data mining has made significant and far-reaching advances over the past three decades. Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of these applications search for patterns in complex structural information. In biomedicine for example, modeling complex biological systems requires linking knowledge across many levels of science, from genes to disease. Further, the data characteristics of the problems have also grown from static to dynamic and spatiotemporal, complete to incomplete, and centralized to distributed, and grow in their scope and size (this is known as big data). The effective integration of big data for decision-making also requires privacy preservation. The contributions to this monograph summarize the advances of data mining in the respective fields. This volume consists of nine chapters that address subjects ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Engineering. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial intelligence. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Engineering. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computational Intelligence. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial Intelligence (incl. Robotics). |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783642408366 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| Uniform title | Studies in Big Data, |
| -- | 2197-6503 ; |
| Volume number/sequential designation | 1 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-642-40837-3 |
| 912 ## - | |
| -- | ZDB-2-ENG |
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