Text Mining (Record no. 75099)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04874nam a22006495i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-0-387-34555-0 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20220801140033.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 100301s2005 xxu| s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9780387345550 |
| -- | 978-0-387-34555-0 |
| 082 04 - CLASSIFICATION NUMBER | |
| Call Number | 006.312 |
| 100 1# - AUTHOR NAME | |
| Author | Weiss, Sholom M. |
| 245 10 - TITLE STATEMENT | |
| Title | Text Mining |
| Sub Title | Predictive Methods for Analyzing Unstructured Information / |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2005. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | XII, 237 p. |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Remark 2 | 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 -- 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. Text mining—the process of searching, retrieving, and analyzing unstructured, natural-language text—is concerned with how to exploit the textual data embedded in these documents. Text Mining presents a comprehensive introduction and overview of the field, integrating related topics (such as artificial intelligence and knowledge discovery and data mining) and providing practical advice on how readers can use text-mining methods to analyze their own data. Emphasizing predictive methods, the book unifies all key areas in text mining: preprocessing, text categorization, information search and retrieval, clustering of documents, and information extraction. In addition, it identifies emerging directions for those looking to do research in the area. Some background in data mining is beneficial, but not essential. Topics and features: * Presents a comprehensive and easy-to-read introduction to text mining * Explores the application and utility of the methods, as well as the optimal techniques for specific scenarios * Provides several descriptive case studies that take readers from problem description to system deployment in the real world * Uses methods that rely on basic statistical techniques, thus allowing for relevance to all languages (not just English) * Includes access to downloadable software (runs on any computer), as well as useful chapter-ending historical and bibliographical remarks, a detailed bibliography, and subject and author indexes This authoritative and highly accessible text, written by a team of authorities on text mining, develops the foundation concepts, principles, and methods needed to expand beyond structured, numeric data to automated mining of text samples. Researchers, computer scientists, and advanced undergraduates and graduates with work and interests in data mining, machine learning, databases, and computational linguistics will find the work an essential resource. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Indurkhya, Nitin. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Zhang, Tong. |
| 700 1# - AUTHOR 2 | |
| Author 2 | Damerau, Fred. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | https://doi.org/10.1007/978-0-387-34555-0 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks |
| 264 #1 - | |
| -- | New York, NY : |
| -- | Springer New York : |
| -- | Imprint: Springer, |
| -- | 2005. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer networks . |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Information storage and retrieval systems. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Natural language processing (Computer science). |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Information technology—Management. |
| 650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Database management. |
| 650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Communication Networks. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Information Storage and Retrieval. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Natural Language Processing (NLP). |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Computer Application in Administrative Data Processing. |
| 650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
| -- | Database Management. |
| 912 ## - | |
| -- | ZDB-2-SCS |
| 912 ## - | |
| -- | ZDB-2-SXCS |
No items available.