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000868431 019__ $$a1099687742$$a1101260580$$a1101296584$$a1103787559$$a1105175155$$a1111288989
000868431 020__ $$a9783030191436$$q(electronic book)
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000868431 0247_ $$a10.1007/978-3-030-19143-6$$2doi
000868431 0248_ $$a10.1007/978-3-030-19
000868431 035__ $$aSP(OCoLC)on1110881903
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000868431 049__ $$aISEA
000868431 050_4 $$aQA76.76.A65$$bQ38 2018
000868431 08204 $$a005.7$$223
000868431 24500 $$aData quality and trust in big data :$$b5th international workshop, QUAT 2018, held in conjunction with WISE 2018, Dubai, UAE, November 12-15, 2018, revised selected papers /$$cedited by Hakim Hacid, Quan Z. Sheng, Tetsuya Yoshida, Azadeh Sarkheyli, Rui Zhou.
000868431 264_1 $$aCham :$$bSpringer International Publishing,$$c2019.
000868431 300__ $$a1 online resource (ix, 137 pages) :$$billustrations.
000868431 336__ $$atext$$btxt$$2rdacontent
000868431 337__ $$acomputer$$bc$$2rdamedia
000868431 338__ $$aonline resource$$bcr$$2rdacarrier
000868431 4901_ $$aInformation Systems and Applications, incl. Internet/Web, and HCI ;$$v11235
000868431 504__ $$aIncludes bibliographical references.
000868431 5050_ $$aA 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 Userâ#x80;#x99;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.
000868431 506__ $$aAccess limited to authorized users.
000868431 520__ $$aThis 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.
000868431 650_0 $$aInformation storage and retrieval systems.
000868431 650_0 $$aArtificial intelligence.
000868431 650_0 $$aComputer system performance.
000868431 7001_ $$aHacid, Hakim,$$eeditor.
000868431 7001_ $$aSheng, Quan Z.,$$eeditor.
000868431 7001_ $$aYoshida, Tetsuya,$$eeditor.
000868431 7001_ $$aSarkheyli, Azadeh,$$eeditor.
000868431 7001_ $$aZhou, Rui,$$eeditor.
000868431 77608 $$iPrint version:$$z3030191427$$z9783030191429$$w(OCoLC)1090994286
000868431 85280 $$bebk$$hSpringerLink
000868431 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-19143-6$$zOnline Access$$91397441.1
000868431 909CO $$ooai:library.usi.edu:868431$$pGLOBAL_SET
000868431 980__ $$aEBOOK
000868431 980__ $$aBIB
000868431 982__ $$aEbook
000868431 983__ $$aOnline
000868431 994__ $$a92$$bISE