Scrap Outline 1, Heres a better topic (IMHO)

Here's an Idea for a topic for a paper:

Research would be in the area of: The viability of a better recommendation engine by using the opensocial API. specifically... recommendations should have at least these dimensions:

1. Credibility: Is the reviewer who he says he is, is that 5 star review for the new camera from a real, satisfied, customer or from the guerrilla marketing department at Sony
   
2. Suitability: Can't think of a better one word description...but does the reviewers taste and skill level match yours?I.e. the kind of Football Helmet Peyton Manning uses, may not be the best football helmet for your Pop Warner aged son, especially if your Pop Warner aged son is a Defensive Lineman instead of a quarterback. Or, if a South Indian says the food at a restaurant was bland, that may mean it is too spicy for you!
   
3. Timeliness: Just because the 1985 Model of the Car was great does not mean the 2009 model was great
4. Reliability: Most products are reviewed as new. How well do the last? How does their performance, effectiveness change over time? This need not be a physical break down, suppose your computer has a brand new 133MHZ mother board, it will work...but...

The paper would bring together research about the fitness of the current OpenSocial API & existing exposed data for the different components of the recommendation engine(Credibility, Suitibility, Timeliness, Reliability). Both the areas where it is suitable and where more API availability/Data is needed would be covered. Lastly the engine's recommendations would be evaluated (with possibly some assumptions based on research) against a published set of Informal test cases. The recommendation would likely be modeled at the algorithm level, and only implemented (in something like Apache Shindig client) if time permits.