Part 2. Deriving intelligence – Collective Intelligence in Action

Part 2. Deriving intelligence

Now that we’ve collected data, in this part we focus on deriving intelligence from it. Part 2 consists of four chapters—an introduction chapter to the data mining process, standards, and toolkits, followed by chapters on developing a text-analysis toolkit, finding patterns through clustering, and making predictions.

Chapter 7 should give you a good overview of the data mining process, along with a basic understanding of WEKA, the open source data mining toolkit, and JDM, the standard data mining API. Next, in chapter 8 we develop a text-processing toolkit to analyze unstructured content. This toolkit is useful for converting text into a format that’s usable by the learning algorithms. Chapter 9 deals with finding patterns of similar items using the process of clustering. Lastly, chapter 10 looks at how we can make predictions by using classification and regression algorithms.

At the end of this part, you should have a good understanding of the data mining process, the various APIs, and the key algorithms for deriving intelligence.