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Working in a hands-on learning environment, led by our Collective Intelligence expert instructor, students will learn about and explore: Architecture for embedding intelligence in your application.Developing metadata about the user and content.Gather intelligence from tagging and build tag clouds.Introduction to intelligent web crawling and Nutch.Harvesting information from the blogosphere.Build a text analysis toolkit leveraging Lucene.Business intelligence and data mining for recommendations and promotions.Leveraging open-source data mining toolkit WEKA and the Java Data Mining (JDM) standard.Incorporating intelligent search in your application.Building a recommendation engine—finding related users and content.Real-world case studies of Amazon, Google News, and Netflix personalization.

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Last Updated

February 5, 2021

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Course Description

In the Web 2.0 era, leveraging the collective power of user contributions, interactions, and feedback is the key to market dominance. A new category of powerful programming techniques lets you discover the patterns, inter-relationships, and individual profiles—the collective intelligence—locked in the data people leave behind as they surf websites, post blogs, and interact with other users.

Collective Intelligence is a course for implementing collective-intelligence concepts using Java. It is the first Java-based course to emphasize the underlying algorithms and technical implementation of vital data gathering and mining techniques like analyzing trends, discovering relationships, and making predictions. It provides a pragmatic approach to personalization by combining content-based analysis with collaborative approaches.

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Course Curriculum

    • What is collective intelligence? 00:00:00
    • CI in web applications 00:00:00
    • Classifying intelligence 00:00:00
    • Architecture for applying intelligence 00:00:00
    • Basics of algorithms for applying CI 00:00:00
    • Forms of user interaction 00:00:00
    • Converting user interaction into collective intelligence 00:00:00
    • Introduction to tagging 00:00:00
    • How to leverage tags 00:00:00
    • Extracting intelligence from user tagging: an example 00:00:00
    • Scalable persistence architecture for tagging 00:00:00
    • Building tag clouds 00:00:00
    • Finding similar tags 00:00:00
    • Content types and integration 00:00:00
    • The main CI-related content types 00:00:00
    • Extracting intelligence step by step 00:00:00
    • Simple and composite content types 00:00:00
    • Introducing the blogosphere 00:00:00
    • Building a framework to search the blogosphere 00:00:00
    • Implementing the base classes 00:00:00
    • Integrating Technorati 00:00:00
    • Integrating Bloglines 00:00:00
    • Integrating providers using RSS 00:00:00
    • Introducing web crawling 00:00:00
    • Building an intelligent crawler step by step 00:00:00
    • Scalable crawling with Nutch 00:00:00
    • Core concepts of data mining 00:00:00
    • Using an open source data mining framework: WEKA 00:00:00
    • Standard data mining API: Java Data Mining (JDM) 00:00:00
    • Building the text analyzers 00:00:00
    • Building the text analysis infrastructure 00:00:00
    • Use cases for applying the framework 00:00:00

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