ID Number: G00171147




Recommendation Technologies: Navigating a Fragmented Media Universe
29 September 2009
 
Mike McGuire   Adam Daum   Andrew Frank  

Search, discovery and recommendation engines designed to increase engagement, and drive content transactions across multiple screens are evolving to meet market needs.








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Table of Contents



    
Analysis

1.0
    
Navigating Nonlinear Content Ecosystems: Search, Discovery and Recommendations
2.0
    
Content Experiences and the Role of Discovery and Recommendation Systems
3.0
    
Essential Elements of Recommendation Systems

3.1
    
Four Data Sources on Which Recommendation Solutions Draw

3.1.1
    
Explicit Metadata
3.1.2
    
Content Analysis
3.1.3
    
Personal Profiling

3.1.3.1
    
Usage History
3.1.3.2
    
Explicit Ratings
3.1.3.3
    
Explicit Profile Disclosures
3.1.4
    
Social Data

3.1.4.1
    
Collaborative Filtering
3.1.4.2
    
Social Graph Filtering
3.2
    
The Identity Management and Implementation Design Challenges

3.2.1
    
User Experience Design and Implementation Challenges
3.3
    
Sample Vendors and Target Markets

3.3.1
    
Music Service Providers
3.3.2
    
TV and Online Video Service Providers
3.3.3
    
Movie Service Providers
4.0
    
Low Consumer Awareness and Usage
5.0
    
Vendor Space and Market Taking Shape in 2009
6.0
    
Conclusion

    
Recommended Reading


List of Figures



Figure 1. 
Three Pillars of Content Acquisition and Their Relationship to Online Ecosystems
 

Figure 2. 
Prompts to Search for Online Audio Content (U.S. Online Consumers)
 

Figure 3. 
Postsearch Behavior for Video Content (U.S. Online Consumers)
 



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Resource Id: 1192214