Text Mining: Classification, Clustering, and Applications Ashok Srivastava, Mehran Sahami
Publisher: Chapman & Hall
This led me to explore probabilistic models for clustering, constrained clustering, and classification with very little labeled data, with applications to text mining. Download Text Mining: Classification, Clustering, and Applications In the section on text mining applications, the book explores web-based information,. Provides state-of-the-art algorithms and techniques for critical tasks in text mining applications, such as clustering, classification, anomaly and trend detection, and stream analysis. Srivastava is the author of many research articles on data mining, machine learning and text mining, and has edited the book, “Text Mining: Classification, Clustering, and Applications” (with Mehran Sahami, 2009). Survey of Text Mining II: Clustering , Classification, and Retrieval . Uncertain Spatio-temporal Applications.- Uncertain Representations and Applications in Sensor Networks.- OLAP over . Text Mining: Classification, Clustering, and Applications book download. Text-mining approaches typically rely on occurrence and co-occurrence statistics of terms and have been successfully applied to a number of problems. This is joint work with Dan Klein, Chris Manning and others. Srivastava, Ashok N., Sahami, Mehran. EbooksFreeDownload.org is a free ebooks site where you can download free books totally free. Link to MnCat Record · Read about this book on Amazon Text mining : classification, clustering, and applications.