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Data quality and trust in big data =...

QUAT (Workshop) (2018 :)

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Data quality and trust in big data = 5th International Workshop, QUAT 2018, held in conjunction with WISE 2018, Dubai, UAE, November 12-15, 2018 : revised selected papers /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data quality and trust in big data/ edited by Hakim Hacid ... [et al.].
Reminder of title:	5th International Workshop, QUAT 2018, held in conjunction with WISE 2018, Dubai, UAE, November 12-15, 2018 : revised selected papers /
remainder title:	QUAT 2018
other author:	Hacid, Hakim.
corporate name:	QUAT (Workshop)
Published:	Cham :Springer International Publishing : : 2019.,
Description:	ix, 137 p. :ill., digital ;24 cm.
[NT 15003449]:	A Novel Data Quality Metric for Minimality -- Automated Schema Quality Measurement in Large-scale Information Systems -- Email Importance Evaluation in Mailing List Discussions -- SETTRUST: Social Exchange Theory Based Context- Aware Trust Prediction in Online Social Networks -- CNR: Cross-Network Recommendation Embedding User's Personality -- Firefly Algorithm with Proportional Adjustment Strategy -- A Formal Taxonomy of Temporal Data Defects -- Data-intensive Computing Acceleration with Python in Xilinx FPGA -- Delone and McLean IS Success Model for Evaluating Knowledge Sharing.
Contained By:	Springer eBooks
Subject:	Big data - Congresses. -
Online resource:	https://doi.org/10.1007/978-3-030-19143-6
ISBN:	9783030191436

Data quality and trust in big data = 5th International Workshop, QUAT 2018, held in conjunction with WISE 2018, Dubai, UAE, November 12-15, 2018 : revised selected papers /
Data quality and trust in big data5th International Workshop, QUAT 2018, held in conjunction with WISE 2018, Dubai, UAE, November 12-15, 2018 : revised selected papers /[electronic resource] :QUAT 2018edited by Hakim Hacid ... [et al.]. - Cham :Springer International Publishing :2019. - ix, 137 p. :ill., digital ;24 cm. - Lecture notes in computer science,112350302-9743 ;. - Lecture notes in computer science ;11235..

A Novel Data Quality Metric for Minimality -- Automated Schema Quality Measurement in Large-scale Information Systems -- Email Importance Evaluation in Mailing List Discussions -- SETTRUST: Social Exchange Theory Based Context- Aware Trust Prediction in Online Social Networks -- CNR: Cross-Network Recommendation Embedding User's Personality -- Firefly Algorithm with Proportional Adjustment Strategy -- A Formal Taxonomy of Temporal Data Defects -- Data-intensive Computing Acceleration with Python in Xilinx FPGA -- Delone and McLean IS Success Model for Evaluating Knowledge Sharing.

This book constitutes revised selected papers from the International Workshop on Data Quality and Trust in Big Data, QUAT 2018, which was held in conjunction with the International Conference on Web Information Systems Engineering, WISE 2018, in Dubai, UAE, in November 2018. The 9 papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with novel ideas and solutions related to the problems of exploring, assessing, monitoring, improving, and maintaining the quality of data and trust for Big Data.

ISBN: 9783030191436

Standard No.: 10.1007/978-3-030-19143-6doiSubjects--Topical Terms:

3166510
Big data
--Congresses.

LC Class. No.: QA76.76.A65 / Q38 2018

Dewey Class. No.: 005.7

Data quality and trust in big data = 5th International Workshop, QUAT 2018, held in conjunction with WISE 2018, Dubai, UAE, November 12-15, 2018 : revised selected papers /
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520 $a This book constitutes revised selected papers from the International Workshop on Data Quality and Trust in Big Data, QUAT 2018, which was held in conjunction with the International Conference on Web Information Systems Engineering, WISE 2018, in Dubai, UAE, in November 2018. The 9 papers presented in this volume were carefully reviewed and selected from 15 submissions. They deal with novel ideas and solutions related to the problems of exploring, assessing, monitoring, improving, and maintaining the quality of data and trust for Big Data.
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