single-column

mega-menu

Browse by Institution Type

Browse by Product Type

Products

Support

Would you like to go to the Gale {{RECOMMENDED_COUNTRY}} site instead?

It looks like you're visiting from {{DETECTED_COUNTRY}}.

main

products

config

Marketing materials, training documents, discovery services

cengage:card

FIND YOUR SALES REPRESENTATIVE

cengage:column

Get marketing materials, training documents, discovery services.

PRODUCT SUPPORT

CUSTOMER SUPPORT

Report technical issues, errors, check system status

TECHNICAL SUPPORT

Manage product preferences, generate usage reports, simplify administrative tasks.

ADMIN TOOLS

support

secondary-primary-menu

About Us

Blogs

Press Center

Events

News

Careers

Our Company

Request a Trial

container

footer-menu

Academic Institutions

K-12

Public Libraries

Government and Special Libraries

Statewide Programs

Institutions

Databases

Primary Sources

Digital Humanities Tools

eLearning

Schools/K-12 Curriculum

Books

Large Print Books by Thorndike Press

Find Your Rep

Product Support

Technical Support

Customer Support

Admin Tools

Accessibility Policy

Partnerships

Contact Us

%1 products have been added to your cart but %2 have been backordered and will be fulfilled when stock is available

Product on backorder

Current quantity limit is [maxProductQuantity], please, navigate to the cart page and change quantity of product

You will be able to resubmit promo in ${countdown} seconds. test

Please note that the taxes displayed on our website are estimated and subject to adjustment. The actual tax charges will be determined and settled during the final invoicing of your order

product-detail-component

Account Information

bundle-connector

cengage:galethorndikeseo

zone3

secondary-account-menu

footer-legal-menu

Terms of use

Privacy

zone2

footer-legal-menu-component

footer

footer-social-menu

Sign Up for Emails

CONNECT WITH GALE

Stay up-to-date with the latest Gale news, exclusive offers, and more.

facebook

linkedin

instagram

youtube

SOCIAL ICONS

footer-social-menu-component

Profile

Orders

Wish List

Fast Order Entry

My Account

header

secondary-storefront-menu

gale-footer

FIND YOUR REP

support-order-2

zone1

You may already have access to Gale content through your institution.

STUDENTS AND RESEARCHERS

support-order-1

International

North America

China

Japan

Latin America

Brazil

Region

Set your region:

header-component

footer-menu-component

Compression Schemes for Mining Large Datasets

ACVPR: COMPRESSION SCHEMES FOR MINING LARGE DATASETS

Information Technology

Computing & Information Technology

Gt Product Group

Binding Format

Marketing Imprint Name

B2B GT

CL Carton Count

Imprint Name

B2B & B2C

This book addresses the challenges of data abstraction generation using a least number of database scans, compressing data through novel lossy and non-lossy schemes, and carrying out clustering and classification directly in the compressed domain. Schemes are presented which are shown to be efficient both in terms of space and time, while simultaneously providing the same or better classification accuracy. Features: describes a non-lossy compression scheme based on run-length encoding of patterns with binary valued features; proposes a lossy compression scheme that recognizes a pattern as a sequence of features and identifying subsequences; examines whether the identification of prototypes and features can be achieved simultaneously through lossy compression and efficient clustering; discusses ways to make use of domain knowledge in generating abstraction; reviews optimal prototype selection using genetic algorithms; suggests possible ways of dealing with big data problems using multiagent systems.

POST SECONDARY FOUR YEAR

COLFR

COLJR

COLSO

COLSR

Duration

Duration Unit Of Measure

Transaction Type

Front Cover.
Other Frontmatter.
Title Page.
Copyright Page.
Preface.
Contents.
Acronyms.
1: Introduction.
2: Data Mining Paradigms.
3: Run-Length-Encoded Compression Scheme.
4: Dimensionality Reduction by Subsequence Pruning.
5: Data Compaction through Simultaneous Selection of Prototypes and Features.
6: Domain Knowledge-Based Compaction.
7: Optimal Dimensionality Reduction.
8: Big Data Abstraction through Multiagent Systems.
Appendix: Intrusion Detection Dataset&#x2014;Binary Representation.
Glossary.
Index.

Compression Schemes for Mining Large Datasets.css-1p8rvzy{position:absolute;padding-left:8px;}

Compression Schemes for Mining Large Datasets