This book evolved from material developed over several years by Anand Rajaraman and Jeff Ullman for a one-quarter course at Stanford. The course CS345A, titled “Web Mining,” was designed as an advanced graduate course, although it has become accessib
The book is based on Stanford Computer Science course CS246: Mining Massive Datasets (and CS345A: Data Mining). The book, like the course, is designed at the undergraduate computer science level with no formal prerequisites. To support deeper explor
The book is based on Stanford Computer Science course CS246: Mining Massive Datasets (and CS345A: Data Mining). The book, like the course, is designed at the undergraduate computer science level with no formal prerequisites. To support deeper explor
Introduction; MapReduce Frequent Itemsets Mining Locality-Sensitive Hashing I Locality-Sensitive Hashing II Clustering Dimensionality Reduction Recommender Systems I Recommender Systems II PageRank Link Spam and Introduction to Social Networks Socia
The ppt is based on Stanford Computer Science course CS246: Mining Massive Datasets (and CS345A: Data Mining). The book, like the course, is designed at the undergraduate computer science level with no formal prerequisites. To support deeper explora
This book evolved from material developed over several years by Anand Raja- raman and Jeff Ullman for a one-quarter course at Stanford. The course CS345A, titled “Web Mining,” was designed as an advanced graduate course, although it has become acces
The book is based on Stanford Computer Science course CS246: Mining Massive Datasets (and CS345A: Data Mining).The book, like the course, is designed at the undergraduate computer science level with no formal prerequisites. To support deeper explora
