Safe Browsing Tool | WOT (Web of Trust)

Add WOT to your browser to protect yourself from online threats that anti-virus software can’t spot Web safety is not just about viruses and malware. WOT’s ratings are powered by a global community of millions of users who rate websites based on their own experiences. Add WOT to you browser for protection against online threats that only real life experience can detect, such as scams, untrustworthy links, and rogue web stores. Reputation ratings boost trust online WOT displays a colored traffic light next to website links to show you which sites people trust for safe searching, surfing and shopping online: green for good, red for bad, and yellow as a warning to be cautious. Safe Browsing Tool | WOT (Web of Trust)
About Meet the Founders A Q&A with Noah and James Why did you build Percolate About
Web Services API
Kleiner-Backed Lockerz Acquires Social Sharing Platform AddToAny Exclusive-Social commerce network Lockerz has acquired social sharing platform AddToAny. Financial terms of the acquisition were not disclosed. AddToAny, which has never raised any outside financing and is profitable, allows users to share and bookmark online content with social networks, news aggregators, email services, and instant messengers. Kleiner-Backed Lockerz Acquires Social Sharing Platform AddToAny
Yelp's Review Filter Explained
6 Tips for Finding Great Content to Share on Twitter 6 Tips for Finding Great Content to Share on Twitter In the land of Twitter, you are known by what you tweet Finding and sharing great content is the key to establishing yourself as a thought leader in the arena of social media. Here are some Twitter tips on how to find and share great content: 1. Do a Twitter search of users to identify and follow thought leaders in your niche. Once you’ve decided what field you would like to establish yourself as a leader in on Twitter, do a Twitter search of users and begin following those who are already sharing content in the space.
Your Social TV Guide | Matcha
The +1 button for websites: recommend content across the web Since we started rolling out the +1 button in March, you’ve been able to recommend content to your friends and contacts directly from Google search results and ads. But sometimes you want to +1 a page while you’re on it. After all, how do you know you want to suggest that recipe for chocolate flan if you haven’t tried it out yet? Today, we’re releasing +1 buttons to the whole web. As a result, you might start seeing +1 appear on sites large and small across the Internet. The +1 button for websites: recommend content across the web
This document briefly describes the technical details of Advogato's trust metric. The basic trust metric evaluates a set of peer certificates, resulting in a set of accounts accepted. These certificates are represented as a graph, with each account as a node, and each certificate as a directed edge. Trust Metric Trust Metric

BOOKS TOOLBOX: 50+ Sites for Book Lovers

Lulu, a book publishing site, is in the news this week. But there are many more sites for book reviews, self-publishing and exchange. Here are more than 50 of our favorites. Disclosure: Lulu currently has an ad campaign running on Mashable. Book Reviews - Search from thousands of books, buy them online and read excellent reviews. BOOKS TOOLBOX: 50+ Sites for Book Lovers
OpenRecommender | What will you share today?
Recommender systems or recommendation systems (sometimes replacing "system" with a synonym such as platform or engine) are a subclass of information filtering system that seek to predict the 'rating' or 'preference' that user would give to an item.[1][2] Recommender systems have become extremely common in recent years, and are applied in a variety of applications. The most popular ones are probably movies, music, news, books, research articles, search queries, social tags, and products in general. However, there are also recommender systems for experts, jokes, restaurants, financial services, life insurance, persons (online dating), and twitter followers .[3] Overview[edit] Recommender system

Recommender system

September 7, 2010 Suggestion graph made with test application Hi, Since last year that I haven’t added any post on my blog, but I would like add new posts. This year I’ll start sharing publishing the work carried out in order to get my degree. The document is currently in spanish. Recommendation’s Engine based on Spread Activation algorithm « Álvaro Brange’s Blog. Recommendation’s Engine based on Spread Activation algorithm « Álvaro Brange’s Blog.
Open Source Recommendation engine
Add recommendations to your website Use our public evaluation instance of easyrec to integrate recommendations into your applications. For further information on how to use the evaluation service have a look at the get started page. recommendation engine recommendation engine