Mining of masive datasets
Jure Leskovec; Anand Rajaraman; Jeffrey D Ullman
- 3RD
- Cambridge : Cambridge University Press , 2020
- 553 p
1. Data mining; 2. MapReduce and the new software stack; 3. Finding similar items; 4. Mining data streams; 5. Link analysis; 6. Frequent itemsets; 7. Clustering; 8. Advertising on the web; 9. Recommendation systems; 10. Mining social-network graphs; 11. Dimensionality reduction; 12. Large-scale machine learning; 13. Neural nets and deep learning
Essential reading for students and practitioners, this book focuses on practical algorithms used to solve key problems in data mining, with exercises suitable for students from the advanced undergraduate level and beyond. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs