Reflection: GroupLens
The paper discusses “GroupLens” as “An Open Architecture for Collaborative Filtering of Netnew”. As I read this articile I began thinking of all the popular recommendation apps that are out there today such as Netflix, Hulu, Amazon,Youtube, etc and realized how they all have the same key fundamental principles:
Openness: There are currently dozens of news clients in common use, each with a strong following among its user community. Any or all of these clients can be adapted to participate in GroupLens. GroupLens also allows for the creation of alternative Better Bit Bureaus that use ratings in different ways to predict user interest in news articles.
Ease of Use: Ratings are easy to form and communicate, and predictions are easy to recognize and interpret. This minimizes the additional burden that collaborative filtering places on users.
Compatibility: The architecture is compatible with existing news mechanisms, Compatibility reduces user overhead in taking advantage of the new tool, and simplifies its introduction into netnews.
Scalability : As the number of users grows, the quality of predictions should improve and the speed not deteriorate. One potential limit to growth will be transport and storage of the ratings, if GroupLens grows very large.
Privacy: Some users would prefer not to have others know what kinds of articles they read and what kinds they like. The Better Bit Bureaus in GroupLens can make effective use of ratings even if they are provided under a pseudonym.
Though I enjoy these recommendations, a part of me would like to see the other spectrum on things that the are the bottom of the recommendation list. Part of me believes I might actually enjoy some of those recommendations. Personally, I enjoy watching and viewing things that are out of the norm, so though it is great to view activities that I may like, I also enjoy the option of viewing things that the recommendation system might not necessary believe is for me. I believe a balance has to be made between allowing users to stay within a certain “bubble” and allowing that user to also branch out and experience things out of the normal from which a system believes they would enjoy.