Ne present 01
Introduction to Recommender Systems What is an RS? [What are different types of recommender systems]
My Project Part 1: Exploring Recommendation Systems look at different recommender systems
- by dif companies
- dif methods
historical vantage-point: start w/ oldest & come to newest what makes a good RS?
- AI/machine learning used in RS
- security/privacy issues?
- multi-agent systems, computer models for trust?
Part 2: Designing a Recommendation System? plan is to design new RS -- use novel topic (e.g. Bryn Mawr course recommendations) or technique (hybrid of existing techniques?) may deem infeasible or may prefer to explore RS research further in that case, will present analysis of current state of affairs re: recommendation systems & suggestions for further improvements
What I’ve Done So Far began reading articles re: RS
- lay articles including Jeffrey O'Brien's The race to create a 'smart' Google -- it's interesting; check it out!!
- began mathy article Gediminas Adomavicius & Alexander Tuzhilin's Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions
- set up Wiki page (notes, sources, thesis description)
- continue reading (& adding to wiki page)
- specifically, look into old/original rec systems
- want to know more about each of the three types of RS (personalized, social, item-based)
- more details on how they work
- look at companies -- how do they explain what they're doing (be wary of "we're so amazing"- type spin)
- any info on classifying/rating rec systems -- how do you know if one is "better" than another?)