Part 1 Gathering data for intelligence

1 Understanding collective intelligence: 1.1 What is collective intelligence?; 1.2 CI in web applications; 1.3 Classifying intelligence; 1.4 Summary; 1.5 Resources
2 Learning from user interactions: 2.1 Architecture for applying intelligence; 2.2 Basics of algorithms for applying CI; 2.3 Forms of user interaction; 2.4 Converting user interaction into collective intelligence; 2.5 Summary; 2.6 Resources
3 Extracting intelligence from tags: 3.1 Introduction to tagging; 3.2 How to leverage tags; 3.3 Extracting intelligence from user tagging: an example; 3.4 Scalable persistence architecture for tagging; 3.5 Building tag clouds; 3.6 Finding similar tags; 3.7 Summary; 3.8 Resources
4 Extracting intelligence from content: 4.1 Content types and integration; 4.2 The main CI-related content types; 4.3 Extracting intelligence step by step; 4.4 Simple and composite content types; 4.5 Summary; 4.6 Resources
5 Searching the blogosphere: 5.1 Introducing the blogosphere; 5.2 Building a framework to search the blogosphere; 5.3 Implementing the base classes; 5.4 Integrating Technorati; 5.5 Integrating Bloglines; 5.6 Integrating providers using RSS; 5.7 Summary; 5.8 Resources
6 Intelligent web crawling: 6.1 Introducing web crawling; 6.2 Building an intelligent crawler step by step; 6.3 Scalable crawling with Nutch; 6.4 Summary; 6.5 Resources

Part 2 Deriving intelligence

7 Data mining: process, toolkits, and standards: 7.1 Core concepts of data mining; 7.2 Using an open source data mining framework: WEKA; 7.3 Standard data mining API: Java Data Mining (JDM); 7.4 Summary; 7.5 Resources
8 Building a text analysis toolkit: 8.1 Building the text analyzers; 8.2 Building the text analysis infrastructure; 8.3 Use cases for applying the framework; 8.4 Summary; 8.5 Resources
9 Discovering patterns with clustering: 9.1 Clustering blog entries; 9.2 Leveraging WEKA for clustering; 9.3 Clustering using the JDM APIs; 9.4 Summary; 9.5 Resources
10 Making predictions: 10.1 Classification fundamentals; 10.2 Classifying blog entries using WEKA APIs; 10.3 Regression fundamentals; 10.4 Regression using WEKA; 10.5 Classification and regression using JDM; 10.6 Summary; 10.7 Resources

11 Intelligent search: 11.1 Search fundamentals; 11.2 Indexing with Lucene; 11.3 Searching with Lucene; 11.4 Useful tools and frameworks; 11.5 Approaches to intelligent search; 11.6 Summary; 11.7 Resources 347
12 Building a recommendation engine: 12.1 Recommendation engine fundamentals; 12.2 Content-based analysis; 12.3 Collaborative filtering; 12.4 Real-world solutions; 12.5 Summary; 12.6 Resources