Language:
English
繁體中文
Help
圖資館首頁
Login
Back
Switch To:
Labeled
|
MARC Mode
|
ISBD
Text miningconcepts, implementation,...
~
Jo, Taeho.
Text miningconcepts, implementation, and big data challenge /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Text miningby Taeho Jo.
Reminder of title:
concepts, implementation, and big data challenge /
Author:
Jo, Taeho.
Published:
Cham :Springer International Publishing :2019.
Description:
xiii, 373 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Data mining.
Online resource:
http://dx.doi.org/10.1007/978-3-319-91815-0
ISBN:
9783319918150$q(electronic bk.)
Text miningconcepts, implementation, and big data challenge /
Jo, Taeho.
Text mining
concepts, implementation, and big data challenge /[electronic resource] :by Taeho Jo. - Cham :Springer International Publishing :2019. - xiii, 373 p. :ill., digital ;24 cm. - Studies in big data,v.452197-6503 ;. - Studies in big data ;v.1..
Part I: Foundation -- Introduction -- Text Indexing -- Text Encoding -- Text Association -- Part II: Text Categorization -- Text Categorization: Conceptual View -- Text Categorization: Approaches -- Text Categorization: Implementation -- Text Categorization: Evaluation -- Part III: Text Clustering -- Text Clustering: Conceptual View -- Text Clustering: Approaches -- Text Clustering: Implementation -- Text Clustering: Evaluation -- Part IV: Advanced Topics -- Text Summarization -- Text Segmentation -- Taxonomy Generation -- Dynamic Document Organization -- References -- Index.
This book discusses text mining and different ways this type of data mining can be used to find implicit knowledge from text collections. The author provides the guidelines for implementing text mining systems in Java, as well as concepts and approaches. The book starts by providing detailed text preprocessing techniques and then goes on to provide concepts, the techniques, the implementation, and the evaluation of text categorization. It then goes into more advanced topics including text summarization, text segmentation, topic mapping, and automatic text management. Presents techniques of preprocessing texts into structured forms; Outlines concepts of text categorization and clustering, their algorithms, and implementation guides; Includes advanced topics such as text summarization, text segmentation, topic mapping, and automatic text management.
ISBN: 9783319918150$q(electronic bk.)
Standard No.: 10.1007/978-3-319-91815-0doiSubjects--Topical Terms:
184440
Data mining.
LC Class. No.: QA76.9.D343 / J683 2019
Dewey Class. No.: 006.312
Text miningconcepts, implementation, and big data challenge /
LDR
:02439nmm a2200325 a 4500
001
550300
003
DE-He213
005
20180607135831.0
006
m d
007
cr nn 008maaau
008
191004s2019 gw s 0 eng d
020
$a
9783319918150$q(electronic bk.)
020
$a
9783319918143$q(paper)
024
7
$a
10.1007/978-3-319-91815-0
$2
doi
035
$a
978-3-319-91815-0
040
$a
GP
$c
GP
041
0
$a
eng
050
4
$a
QA76.9.D343
$b
J683 2019
072
7
$a
TJK
$2
bicssc
072
7
$a
TEC041000
$2
bisacsh
082
0 4
$a
006.312
$2
23
090
$a
QA76.9.D343
$b
J62 2019
100
1
$a
Jo, Taeho.
$3
830094
245
1 0
$a
Text mining
$h
[electronic resource] :
$b
concepts, implementation, and big data challenge /
$c
by Taeho Jo.
260
$a
Cham :
$b
Springer International Publishing :
$b
Imprint: Springer,
$c
2019.
300
$a
xiii, 373 p. :
$b
ill., digital ;
$c
24 cm.
490
1
$a
Studies in big data,
$x
2197-6503 ;
$v
v.45
505
0
$a
Part I: Foundation -- Introduction -- Text Indexing -- Text Encoding -- Text Association -- Part II: Text Categorization -- Text Categorization: Conceptual View -- Text Categorization: Approaches -- Text Categorization: Implementation -- Text Categorization: Evaluation -- Part III: Text Clustering -- Text Clustering: Conceptual View -- Text Clustering: Approaches -- Text Clustering: Implementation -- Text Clustering: Evaluation -- Part IV: Advanced Topics -- Text Summarization -- Text Segmentation -- Taxonomy Generation -- Dynamic Document Organization -- References -- Index.
520
$a
This book discusses text mining and different ways this type of data mining can be used to find implicit knowledge from text collections. The author provides the guidelines for implementing text mining systems in Java, as well as concepts and approaches. The book starts by providing detailed text preprocessing techniques and then goes on to provide concepts, the techniques, the implementation, and the evaluation of text categorization. It then goes into more advanced topics including text summarization, text segmentation, topic mapping, and automatic text management. Presents techniques of preprocessing texts into structured forms; Outlines concepts of text categorization and clustering, their algorithms, and implementation guides; Includes advanced topics such as text summarization, text segmentation, topic mapping, and automatic text management.
650
0
$a
Data mining.
$3
184440
650
0
$a
Big data.
$3
609582
650
1 4
$a
Engineering.
$3
210888
650
2 4
$a
Communications Engineering, Networks.
$3
273745
650
2 4
$a
Computational Intelligence.
$3
338479
650
2 4
$a
Data Mining and Knowledge Discovery.
$3
275288
650
2 4
$a
Information Storage and Retrieval.
$3
274190
650
2 4
$a
Big Data/Analytics.
$3
742047
710
2
$a
SpringerLink (Online service)
$3
273601
773
0
$t
Springer eBooks
830
0
$a
Studies in big data ;
$v
v.1.
$3
675357
856
4 0
$u
http://dx.doi.org/10.1007/978-3-319-91815-0
950
$a
Engineering (Springer-11647)
based on 0 review(s)
ALL
電子館藏
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
Usage Class
Loan Status
No. of reservations
Opac note
Attachments
000000164368
電子館藏
1圖書
電子書
EB QA76.9.D343 J62 2019 2019
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
Multimedia
Multimedia file
http://dx.doi.org/10.1007/978-3-319-91815-0
Reviews
Add a review
and share your thoughts with other readers
Export
pickup library
Processing
...
Change password
Login