What's REC.MN?

REC.MN (?recommend?) is the first Truly-Social Social Recommendation Engine.

What can I use REC.MN for?

The short answer: you use REC.MN to get and give recommendations .

The longer answer: use REC.MN to:

1. Search for recommendations from your friends and other reputable people.
2. Ask for recommendations from your friends.
3. Get recommended by friends, colleagues, customers, or fans.
4. Thank people for recommending things to you.
5. Share your recommendations with friends and others with your personalized short URL.
6. Track your recommendations and see how many have viewed, liked, or re-recommended them.
7. Discover people who are knowledgeable, influential on topics you care about.
8. Build your influence online, and monetize it in the near future!

What Makes REC.MN ?Truly Social? ?

Real-world recommendations from your real-world friends, family, and others you trust. Not just what's-trending, follow-the-crowd stuff.

REC.MN's design principle is People First, Content Second . This means we help you discover recommendations and content through people you trust or care about. Not the other way around.

We apply machine-learning algorithms to track and measure reputation and other trust metrics that are personalized to you and your social networks. The more you and your friends use REC.MN, the more helpful it becomes at filtering out noise (irrelevant stuff from people you don't know or trust). This way, REC.MN can give you really valuable recommendations for people and things you care about.

What Makes REC.MN ?Smart? ?

The more you use it, the more helpful it becomes for you.

Whose recommendations do you follow? This depends on many factors. Do you trust the person? How well do you know them? How well do they know you? Do you have confidence in their judgment? What is the relevant topic? How important is this decision? Etc. If you're traveling to New York and need a recommendation for a good hotel, you'll probably weigh the advice of the friend in Manhattan more than that of your CS professor at Stanford, whose opinion on what grad school to go to you'll probably value more.

Static social graphs showing connections between people are nice, but not enough. The REC.MN social-recommendation engine analyzes multiple numeric and semantic factors with a great many data points to compute dynamic (how recent?), weighted (how influential or knowlegeable?), directed (who influences whom?), semantic (what's the topic?) graphs of knowledge and influence personalized to you. When you search for a recommendation, the answers that come back are filtered and ranked by these graphs.

In short, the REC.MN engine does the heavy lifting to bring you that best recommendation you need to make that decision, large or small.