OpenRecommender v1.0 released!
This is a post to announce the ALPHA release of OpenRecommender, version 1.0.
Project logo w. Chinese characters for 'Trust'
Have you ever wondered if there was a better way to find information on the web? Before today, there has been lots of ways from targeted search to surfing aimlessly, or from social sharing via SNS platforms like Facebook or Google+ to required reading assigned by professors, co-workers or managers by email (i.e. “Recommended reading”). Even “stumbling” across interesting content via tools like StumbleUpon, Digg and Delicious is also commonly mistaken as being a form of “recommendation” service. These tools are not Recommendation Engines though, they are most accurately described as Social Bookmarking tools (i.e. users must manually save something for later, or, “mark their place” so they can take up where they left off in browsing/reading). In fact these tools have some opportunity to become web-wide Recommendation Engines since links can be submitted on any topic, and some (such as Digg) even have “Related Content” suggestions that group item or user similarity, however the problem is that similarity is just one small measure of relevance for true recommendations. OpenRecommender identifies 15 algorithm types for generating high quality recommendations. The more the merrier, in fact, so any algorithm could be used as long as it can be ranked in real-time.
Today, I’m proud to be able to share a first look at a new approach that represents a “Recommendation” more completely than ever before. The OpenRecommender project ALPHA release realizes the first step in a talk I gave exactly one year ago at AWOSS 2010:
BC$ = Behavior, Content, Money
The goal of the BC$ project is to raise awareness and make changes with respect to the three pillars of information freedom - Behavior (pursuit of interests and passions), Content (sharing/exchanging ideas in various formats), Money (fairness and accessibility) - bringing to light the fact that:
1. We regularly hand over our browser histories, search histories and daily online activities to companies that want our money, or, to benefit from our use of their services with lucrative ad deals or sales of personal information.
2. We create and/or consume interesting content on their services, but we aren't adequately rewarded for our creative efforts or loyalty.
3. We pay money to be connected online (and possibly also over mobile), yet we lose both time and money by allowing companies to market to us with unsolicited advertisements, irrelevant product offers and unfairly structured service pricing plans.