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| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20140310151116.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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140220s2010 xxk| s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781849962261 |
|
978-1-84996-226-1 |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QA76.9.D343 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.312 |
| Edition number |
23 |
| 264 #1 - |
|---|
| -- |
London : |
| -- |
Springer London : |
| -- |
Imprint: Springer, |
| -- |
2010. |
| 912 ## - |
|---|
| -- |
ZDB-2-SCS |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Weiss, Sholom M. |
| Relator term |
author. |
| 245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE |
|---|
| Title |
Fundamentals of Predictive Text Mining |
| Medium |
[electronic resource] / |
| Statement of responsibility, etc |
by Sholom M. Weiss, Nitin Indurkhya, Tong Zhang. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
XIV, 283p. |
| Other physical details |
online resource. |
| 440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE |
|---|
| Title |
Texts in Computer Science, |
| International Standard Serial Number |
1868-0941 |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Overview of Text Mining -- From Textual Information to Numerical Vectors -- Using Text for Prediction -- Information Retrieval and Text Mining -- Finding Structure in a Document Collection -- Looking for Information in Documents -- Data Sources for Prediction: Databases, Hybrid Data and the Web -- Case Studies -- Emerging Directions. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
One consequence of the pervasive use of computers is that most documents originate in digital form. Widespread use of the Internet makes them readily available. Text mining - the process of analyzing unstructured natural-language text – is concerned with how to extract information from these documents. Developed from the authors' highly successful Springer reference on text mining, Fundamentals of Predictive Text Mining is an introductory textbook and guide to this rapidly evolving field. Integrating topics spanning the varied disciplines of data mining, machine learning, databases, and computational linguistics, this uniquely useful book also provides practical advice for text mining. In-depth discussions are presented on issues of document classification, information retrieval, clustering and organizing documents, information extraction, web-based data-sourcing, and prediction and evaluation. Background on data mining is beneficial, but not essential. Where advanced concepts are discussed that require mathematical maturity for a proper understanding, intuitive explanations are also provided for less advanced readers. Topics and features: Presents a comprehensive, practical and easy-to-read introduction to text mining Includes chapter summaries, useful historical and bibliographic remarks, and classroom-tested exercises for each chapter Explores the application and utility of each method, as well as the optimum techniques for specific scenarios Provides several descriptive case studies that take readers from problem description to systems deployment in the real world Includes access to industrial-strength text-mining software that runs on any computer. Describes methods that rely on basic statistical techniques, thus allowing for relevance to all languages (not just English) Contains links to free downloadable software and other supplementary instruction material Fundamentals of Predictive Text Mining is an essential resource for IT professionals and managers, as well as a key text for advanced undergraduate computer science students and beginning graduate students. Dr. Sholom M. Weiss is a Research Staff Member with the IBM Predictive Modeling group, in Yorktown Heights, New York, and Professor Emeritus of Computer Science at Rutgers University. Dr. Nitin Indurkhya is Professor at the School of Computer Science and Engineering, University of New South Wales, Australia, as well as founder and president of data-mining consulting company Data-Miner Pty Ltd. Dr. Tong Zhang is Associate Professor at the Department of Statistics and Biostatistics at Rutgers University, New Jersey. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Computer science. |
|
|---|
| Topical term or geographic name as entry element |
Database management. |
|
|---|
| Topical term or geographic name as entry element |
Data mining. |
|
|---|
| Topical term or geographic name as entry element |
Information storage and retrieval systems. |
|
|---|
| Topical term or geographic name as entry element |
Text processing (Computer science. |
|
|---|
| Topical term or geographic name as entry element |
Information systems. |
|
|---|
| Topical term or geographic name as entry element |
Computer Science. |
|
|---|
| Topical term or geographic name as entry element |
Data Mining and Knowledge Discovery. |
|
|---|
| Topical term or geographic name as entry element |
Document Preparation and Text Processing. |
|
|---|
| Topical term or geographic name as entry element |
Computer Appl. in Administrative Data Processing. |
|
|---|
| Topical term or geographic name as entry element |
Information Storage and Retrieval. |
|
|---|
| Topical term or geographic name as entry element |
Database Management. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Indurkhya, Nitin. |
| Relator term |
author. |
|
|---|
| Personal name |
Zhang, Tong. |
| Relator term |
author. |
| 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 |
9781849962254 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
http://dx.doi.org/10.1007/978-1-84996-226-1 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
E-Book |
