Notice bibliographique
- Notice
Type(s) de contenu et mode(s) de consultation : Texte noté : sans médiation
Auteur(s) : Leskovec, Jurij (1980-....)
Rajaraman, Anand
Ullman, Jeffrey D. (1942-....)
Titre(s) : Mining of massive datasets [Texte imprimé] / Jure Leskovec,... Anand Rajaraman,... Jeffrey David Ullman,...
Édition : 3e ed.
Publication : Cambridge : Cambridge university press, copyright 2020
Description matérielle : 1 vol. (XI-553 p.) : ill. ; 26 cm
Note(s) : Notes bibliogr.
"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"
Sujet(s) : Exploration de données
Données massives
Indice(s) Dewey :
006.312 (23e éd.) = Exploration des données (informatique)
Identifiants, prix et caractéristiques : ISBN 9781108476348 (br.)
Identifiant de la notice : ark:/12148/cb46538495b
Notice n° :
FRBNF46538495
(notice reprise d'un réservoir extérieur)
Table des matières : Data 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 ; Neural nets and deep learning.
