000			02533nam a22003738i 4500
001			CR9781139924801
003			UkCbUP
005			20200124160250.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			140224s2014||||enk o ||1 0|eng|d
020			_a9781139924801 (ebook)
020			_z9781107077232 (hardback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aHF5415.125 _b.L46 2014
082	0	0	_a006.312 _223
100	1		_aLeskovec, Jurij, _eauthor.
245	1	0	_aMining of massive datasets / _cJure Leskovec, Anand Rajaraman, Jeffrey David Ullman, Standford University.
250			_aSecond edition.
264		1	_aCambridge : _bCambridge University Press, _c2014.
300			_a1 online resource (xi, 467 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505	0		_aData mining -- MapReduce and the new software stack -- Finding similar items -- Mining data streams -- Link analysis -- Frequent itemsets -- Clustering -- Advertising on the Web -- Recommendation systems -- Mining social-network graphs -- Dimensionality reduction -- Large-scale machine learning.
520			_aWritten by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. 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.
650		0	_aData mining.
650		0	_aBig data.
700	1		_aRajaraman, Anand, _eauthor.
700	1		_aUllman, Jeffrey D., _d1942- _eauthor.
776	0	8	_iPrint version: _z9781107077232
856	4	0	_uhttps://doi.org/10.1017/CBO9781139924801
999			_c519409 _d519407