Mining of massive datasets. (Record no. 50166)

MARC details
000 -LEADER
fixed length control field 01851nam a22002417a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20180917152913.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 180917b xxu||||| |||| 00| 0 eng d
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 9781316638491
028 ## - DISTRIBUTOR NAME
Distributor Name Atlantic Publishers & Distributors (P)LTD.
Distributor address ;7/22,Anasri Road, Daryaganj,New Delhi-110002
Bill Number ;1082225
Bill Date ;05/09/2018
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.312 LES
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Jurij Leskovec
-- ; Anand Rajaraman
-- ; Jeffrey D Ullman
245 ## - TITLE STATEMENT
Title Mining of massive datasets.
Statement of responsibility, etc /Jurij Leskovec
250 ## - EDITION STATEMENT
Edition statement 2nd edition
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Cambridge
Name of publisher, distributor, etc : Cambridge University Press
Date of publication, distribution, etc , 2014.
300 ## - PHYSICAL DESCRIPTION
Extent xii, 467 pages
Dimensions ;24 cm.
365 ## - TRADE PRICE
Price amount 649
505 ## - FORMATTED CONTENTS NOTE
Contents note Data mining --<br/>MapReduce and the new software stack --<br/>Finding similar items --<br/>Mining data streams --<br/>Link analysis --<br/>Frequent itemsets --<br/>Clustering --<br/>Advertising on the Web --<br/>Recommendation systems --<br/>Mining social-network graphs --<br/>Dimensionality reduction --<br/>Large-scale machine learning.
520 ## - SUMMARY, ETC.
Summary, etc <br/>This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the map-reduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream processing algorithms for mining data that arrives too fast for exhaustive processing. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets and clustering. This second edition includes new and extended coverage on social networks, machine learning and dimensionality reduction. It includes a range of over 150 challenging exercises.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Science
655 ## - INDEX TERM--GENRE/FORM
Genre/form data or focus term Data mining
Non-focus term Big data
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Anand Rajaraman; Jeffrey D Ullman
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Cost, normal purchase price Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type Total Renewals Date checked out
    Dewey Decimal Classification   Not For Loan SNU LIBRARY SNU LIBRARY 17/09/2018 649.00   006.312 LES 25667 17/09/2018 17/09/2018 Books    
    Dewey Decimal Classification     SNU LIBRARY SNU LIBRARY 17/09/2018 649.00   006.312 LES 25668 17/09/2018 17/09/2018 Books    
    Dewey Decimal Classification     SNU LIBRARY SNU LIBRARY 17/09/2018 649.00   006.312 LES 25669 17/09/2018 17/09/2018 Books    
    Dewey Decimal Classification     SNU LIBRARY SNU LIBRARY 17/09/2018 649.00   006.312 LES 25670 17/09/2018 17/09/2018 Books    
    Dewey Decimal Classification     SNU LIBRARY SNU LIBRARY 17/09/2018 649.00 4 006.312 LES 25671 23/08/2024 17/09/2018 Books 7 12/01/2024

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