"Principles of Data Mining" explores the extraction of valuable information from vast amounts of unprocessed data. We cover both fundamental and advanced techniques, making our book an essential resource for businesses investing in this technology.
We introduce the basics of data mining, such as cluster analysis, association rules, OLAP, concept definition, data preparation, classification, and prediction. Additionally, we delve into sophisticated methods, including information extraction from complex sources beyond relational databases, such as time-series, spatial, object, and multimedia databases. We also examine the collection of information from various online sources and its transformation into a usable form.
Our chapters are structured to function as separate sections, allowing flexibility for educators to present lessons in any sequence. Our objective is to equip readers with the background knowledge needed to apply data mining to real-world situations by presenting core ideas and methods for each topic.
With advancements in the field, our book delves deeper into big data and includes updated chapters reflecting these developments. "Principles of Data Mining" is a valuable guide for anyone looking to leverage data mining for business success.