000			02646cam a22003618i 4500
001			21476833
005			20250821101949.0
008			200323s2020 nyu 001 0 eng
010			_a 2020012035
020			_a9781108476348 _q(hardback)
035			_a21476833
040			_aDDC _beng _erda _cDLC
042			_apcc
082	0	4	_a006.312 LEM
100	1		_aLeskovec, Jurij, _eauthor.
245	1	0	_aMining of massive datasets / _cJure Leskovec, Anand Rajaraman, Jeffrey David Ullman.
250			_aThird edition.
263			_a2006
264		1	_aNew York, NY : _bCambridge University Press, _c2020.
300			_axi, 553 p.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
365			_cGBP _d68.00
500			_aIncludes index.
520			_a"The Web, social media, mobile activity, sensors, Internet commerce, and many other modern applications provide 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 used on even the largest datasets. It begins with a discussion of the MapReduce framework and related techniques for efficient parallel programming. The tricks of locality-sensitive hashing are explained. This body of knowledge, which deserves to be more widely known, is essential when seeking similar objects in a very large collection without having to compare each pair of objects. Stream-processing algorithms for mining data that arrives too fast for exhaustive processing are also explained. The PageRank idea and related tricks for organizing the Web are covered next. Other chapters cover the problems of finding frequent itemsets and clustering, each from the point of view that the data is too large to fit in main memory. Two applications: recommendation systems and Web advertising, each vital in e-commerce, are treated in detail. Later chapters cover algorithms for analyzing social-network graphs, compressing large-scale data, and machine learning. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs. Written by leading authorities in database and Web technologies, it is essential reading for students and practitioners alike"-- _cProvided by publisher.
650		0	_aData mining.
700	1		_aRajaraman, Anand, _eauthor.
700	1		_aUllman, Jeffrey D., _d1942- _eauthor.
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cBK _n0
999			_c8088 _d8088