MARC details
000 -LEADER |
fixed length control field |
02217nam a22002895i 4500 |
001 - CONTROL NUMBER |
control field |
20306424 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
EG-ScBUE |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20200305144639.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
180125t20182018sz a f b 001 0 eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9783319735306 |
040 ## - CATALOGING SOURCE |
Original cataloging agency |
DLC |
Language of cataloging |
eng |
Description conventions |
rda |
Transcribing agency |
DLC |
Modifying agency |
EG-ScBUE |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
006.31 |
Item number |
AGG |
Edition number |
22 |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Aggarwal, Charu C., |
Relator term |
author. |
245 10 - TITLE STATEMENT |
Title |
Machine learning for text / |
Statement of responsibility, etc |
Charu C. Aggarwal. |
264 #1 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Place of publication, distribution, etc |
Cham, Switzerland : |
Name of publisher, distributor, etc |
Springer / Springer International Publishing, |
Date of publication, distribution, etc |
[2018] |
264 #4 - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
Date of publication, distribution, etc |
c2018 |
300 ## - PHYSICAL DESCRIPTION |
Extent |
xxiii, 493 pages : |
Other physical details |
illustrations ; |
Dimensions |
28 cm |
336 ## - CONTENT TYPE |
Content type term |
text |
Content type code |
txt |
Source |
rdacontent |
337 ## - MEDIA TYPE |
Media type term |
unmediated |
Media type code |
n |
Source |
rdamedia |
338 ## - CARRIER TYPE |
Carrier type term |
volume |
Carrier type code |
nc |
Source |
rdacarrier |
520 ## - SUMMARY, ETC. |
Summary, etc |
Text analytics is a field that lies on the interface of information retrieval, machine learning, and natural language processing. This book carefully covers a coherently organized framework drawn from these intersecting topics. The chapters of this book span three broad categories: 1. Basic algorithms: Chapters 1 through 8 discuss the classical algorithms for text analytics such as preprocessing, similarity computation, topic modeling, matrix factorization, clustering, classification, regression, and ensemble analysis. 2. Domain-sensitive learning: Chapters 8 and 9 discuss learning models in heterogeneous settings such as a combination of text with multimedia or Web links. The problem of information retrieval and Web search is also discussed in the context of its relationship with ranking and machine learning methods. 3. Sequence-centric mining: Chapters 10 through 14 discuss various sequence-centric and natural language applications, such as feature engineering, neural language models, deep learning, text summarization, information extraction, opinion mining, text segmentation, and event detection. This book covers text analytics and machine learning topics from the simple to the advanced. Since the coverage is extensive, multiple courses can be offered from the same book, depending on course level. |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Machine learning. |
Source of heading or term |
BUEsh |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Text processing (Computer science) |
Source of heading or term |
BUEsh |
9 (RLIN) |
7933 |
653 ## - INDEX TERM--UNCONTROLLED |
Resource For college |
Informatics and Computer Science |
Arrived date list |
March2020 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Source of classification or shelving scheme |
Dewey Decimal Classification |
Koha item type |
Book - Borrowing |