Data Mining

Computers & Technology

Jiawei Han

Software

Morgan Kaufmann Publishers Inc,US

Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems)

Jian Pei

Micheline Kamber

Morgan Kaufmann

Hanghang Tong

The ""big data"" era is characterized by an explosion of information in the form of digital data collections, ranging from scientific knowledge, to social media, news, and everyone's daily life. Examples of such collections include scientific publications, enterprise logs, news articles, social media, and general web pages. Valuable knowledge about multi-typed entities is often hidden in the unstructured or loosely structured, interconnected data. Mining latent structures around entities uncovers hidden knowledge such as implicit topics, phrases, entity roles and relationships. In this monograph, we investigate the principles and methodologies of mining latent entity structures from massive unstructured and interconnected data. We propose a text-rich information network model for modeling data in many different domains. This leads to a series of new principles and powerful methodologies for mining latent structures, including (1) latent topical hierarchy, (2) quality topical phrases, (3) entity roles in hierarchical topical communities, and (4) entity relations. This book also introduces applications enabled by the mined structures and points out some promising research directions.

Mining Latent Entity Structures (Synthesis Lectures on Data Mining and Knowledge Discovery)

Chi, Wang

Databases & Big Data

Morgan Claypool

Key features whether you are a seasoned professional or a new student of data mining, this book has much to offer you: a comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business data. Updates that incorporate input from readers, changes in the field, and more material on statistics and machine learning. Dozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projects. Complete classroom support for instructors at www.mkp.com/datamining2e companion site. Description our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the world wide web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge. Like the first edition, voted the most popular data mining book by kd nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data- including stream data, sequence data, graph structured data, social network data, and multi-relational data. Readership database professionals and researchers, data mining professionals;

Data Mining-Concepts and Techniques, 2e

Jiawei

Elsevier Science

Data Mining: Concepts and Techniques

Micheline Kimber

Elsevier

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Books by Jiawei Han