Mining of massive datasets:
Written 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 prac...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2014
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| Ausgabe: | Second edition |
| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 TUM01 TUM02 UBM01 UPA01 URL des Erstveröffentlichers |
| Zusammenfassung: | Written 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 |
| Beschreibung: | 1 online resource (xi, 467 pages) |
| ISBN: | 9781139924801 |
| DOI: | 10.1017/CBO9781139924801 |
Internformat
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| indexdate | 2024-07-10T07:39:18Z |
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| isbn | 9781139924801 |
| language | English |
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| spelling | Leskovec, Jurij Verfasser aut Mining of massive datasets Jure Leskovec (Standford University), Anand Rajaraman (Milliways Labs), Jeffrey David Ullman (Standford University) Second edition Cambridge Cambridge University Press 2014 1 online resource (xi, 467 pages) txt rdacontent c rdamedia cr rdacarrier Written 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 Data mining Big data Data Mining (DE-588)4428654-5 gnd rswk-swf Big Data (DE-588)4802620-7 gnd rswk-swf Big Data (DE-588)4802620-7 s Data Mining (DE-588)4428654-5 s DE-604 Rajaraman, Anand Sonstige oth Ullman, Jeffrey D. 1942- Sonstige (DE-588)123598230 oth Erscheint auch als Druck-Ausgabe 978-1-107-07723-2 https://doi.org/10.1017/CBO9781139924801 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Leskovec, Jurij Mining of massive datasets Data mining Big data Data Mining (DE-588)4428654-5 gnd Big Data (DE-588)4802620-7 gnd |
| subject_GND | (DE-588)4428654-5 (DE-588)4802620-7 |
| title | Mining of massive datasets |
| title_auth | Mining of massive datasets |
| title_exact_search | Mining of massive datasets |
| title_full | Mining of massive datasets Jure Leskovec (Standford University), Anand Rajaraman (Milliways Labs), Jeffrey David Ullman (Standford University) |
| title_fullStr | Mining of massive datasets Jure Leskovec (Standford University), Anand Rajaraman (Milliways Labs), Jeffrey David Ullman (Standford University) |
| title_full_unstemmed | Mining of massive datasets Jure Leskovec (Standford University), Anand Rajaraman (Milliways Labs), Jeffrey David Ullman (Standford University) |
| title_short | Mining of massive datasets |
| title_sort | mining of massive datasets |
| topic | Data mining Big data Data Mining (DE-588)4428654-5 gnd Big Data (DE-588)4802620-7 gnd |
| topic_facet | Data mining Big data Data Mining Big Data |
| url | https://doi.org/10.1017/CBO9781139924801 |
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