東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Data, engineering and applications.....

Shukla, Rajesh Kumar.

Linked to FindBook

Google Book

Amazon

博客來

Data, engineering and applications.. Volume 1

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data, engineering and applications./ edited by Rajesh Kumar Shukla ... [et al.].
other author:	Shukla, Rajesh Kumar.
Published:	Singapore :Springer Singapore : : 2019.,
Description:	viii, 191 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	A review of Recommender System and related Dimensions -- Collaborative Filtering Techniques in Recommendation Systems -- Predicting Users' Interest through ELM basedCollaborative Filtering -- Application of Community Detection Technique in Text Mining -- Sentiment Analysis on WhatsApp Group Chat using R -- A Recent Survey on Information Hiding Techniques -- Investigation of Feature Selection Techniques on Performance of Automatic Text Categorization -- Identiﬁcation and Analysis of Future User Interactions Using Some Link Prediction Methods in Social Networks -- Sentiment Prediction of Facebook Status updates of youngsters -- Logistic Regression for the Diagnosis of Cervical Cancer -- Automatic Examination Timetable Scheduling Using Particle Swarm Optimization and Local Search Algorithm -- Personality Trait Identification for Written Texts Using MLNB -- Deep neural network compression via knowledge distillation for embedded vision applications.
Contained By:	Springer eBooks
Subject:	Data mining. -
Online resource:	https://doi.org/10.1007/978-981-13-6347-4
ISBN:	9789811363474

Data, engineering and applications.. Volume 1
Data, engineering and applications.Volume 1[electronic resource] /edited by Rajesh Kumar Shukla ... [et al.]. - Singapore :Springer Singapore :2019. - viii, 191 p. :ill. (some col.), digital ;24 cm.

A review of Recommender System and related Dimensions -- Collaborative Filtering Techniques in Recommendation Systems -- Predicting Users' Interest through ELM basedCollaborative Filtering -- Application of Community Detection Technique in Text Mining -- Sentiment Analysis on WhatsApp Group Chat using R -- A Recent Survey on Information Hiding Techniques -- Investigation of Feature Selection Techniques on Performance of Automatic Text Categorization -- Identiﬁcation and Analysis of Future User Interactions Using Some Link Prediction Methods in Social Networks -- Sentiment Prediction of Facebook Status updates of youngsters -- Logistic Regression for the Diagnosis of Cervical Cancer -- Automatic Examination Timetable Scheduling Using Particle Swarm Optimization and Local Search Algorithm -- Personality Trait Identification for Written Texts Using MLNB -- Deep neural network compression via knowledge distillation for embedded vision applications.

This book presents a compilation of current trends, technologies, and challenges in connection with Big Data. Many fields of science and engineering are data-driven, or generate huge amounts of data that are ripe for the picking. There are now more sources of data than ever before, and more means of capturing data. At the same time, the sheer volume and complexity of the data have sparked new developments, where many Big Data problems require new solutions. Given its scope, the book offers a valuable reference guide for all graduate students, researchers, and scientists interested in exploring the potential of Big Data applications.

ISBN: 9789811363474

Standard No.: 10.1007/978-981-13-6347-4doiSubjects--Topical Terms:

562972
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Data, engineering and applications.. Volume 1
LDR:02590nmm a2200325 a 4500 001 2180314
003 DE-He213
005 20190318165505.0
006 m d
007 cr nn 008maaau
008 191122s2019 si s 0 eng d
020 $a 9789811363474 $q (electronic bk.)
020 $a 9789811363467 $q (paper)
024 7 $a 10.1007/978-981-13-6347-4 $2 doi
035 $a 978-981-13-6347-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D343
072 7 $a UN $2 bicssc
072 7 $a COM021000 $2 bisacsh
072 7 $a UN $2 thema
082 0 4 $a 006.312 $2 23
090 $a QA76.9.D343 $b D232 2019
245 0 0 $a Data, engineering and applications. $n Volume 1 $h [electronic resource] / $c edited by Rajesh Kumar Shukla ... [et al.].
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2019.
300 $a viii, 191 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a A review of Recommender System and related Dimensions -- Collaborative Filtering Techniques in Recommendation Systems -- Predicting Users' Interest through ELM basedCollaborative Filtering -- Application of Community Detection Technique in Text Mining -- Sentiment Analysis on WhatsApp Group Chat using R -- A Recent Survey on Information Hiding Techniques -- Investigation of Feature Selection Techniques on Performance of Automatic Text Categorization -- Identiﬁcation and Analysis of Future User Interactions Using Some Link Prediction Methods in Social Networks -- Sentiment Prediction of Facebook Status updates of youngsters -- Logistic Regression for the Diagnosis of Cervical Cancer -- Automatic Examination Timetable Scheduling Using Particle Swarm Optimization and Local Search Algorithm -- Personality Trait Identification for Written Texts Using MLNB -- Deep neural network compression via knowledge distillation for embedded vision applications.
520 $a This book presents a compilation of current trends, technologies, and challenges in connection with Big Data. Many fields of science and engineering are data-driven, or generate huge amounts of data that are ripe for the picking. There are now more sources of data than ever before, and more means of capturing data. At the same time, the sheer volume and complexity of the data have sparked new developments, where many Big Data problems require new solutions. Given its scope, the book offers a valuable reference guide for all graduate students, researchers, and scientists interested in exploring the potential of Big Data applications.
650 0 $a Data mining. $3 562972
650 0 $a Machine learning. $3 533906
650 1 4 $a Big Data. $3 3134868
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
650 2 4 $a Artificial Intelligence. $3 769149
700 1 $a Shukla, Rajesh Kumar. $3 3386258
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
856 4 0 $u https://doi.org/10.1007/978-981-13-6347-4
950 $a Computer Science (Springer-11645)