The Firefly website was created by Firefly Network, Inc.(originally known as Agents Inc.) The company was founded in March 1995 by a group of engineers from MIT Media Lab and some business people from Harvard Business School, including Pattie Maes (Media Lab professor), Upendra Shardanand, Nick Grouf, Max Metral, David Waxman and Yezdi Lashkari. At the Media Lab, under the supervision of Maes, some of the engineers built a music recommendation system called HOMR (Helpful Online Music Recommendation Service; preceded by RINGO, an email-based system) which used collaborative filtering to help navigate the music domain to find other artists and albums that a user might like. Firefly's core technology was based on the work done on HOMR.
The Firefly website was launched in October 1995. It went through several iterations but remained a community throughout. It was initially created as a community for users to navigate and discover new musical artists and albums. Later it was changed to allow users to discover movies, websites, and communities as well.
Firefly technology was adopted by a number of well-known businesses, including the recommendation engine for barnesandnoble.com, ZDnet, launch.com (later purchased by Yahoo) and MyYahoo.
Since Firefly was amassing large amounts of profile data from its users, privacy became a big concern of the company. They worked with the Federal Government to help define consumer privacy protection in the digital age. They also were key contributors to OPS (Open Profiling Standard), a recommendation to the W3C (along with Netscape and VeriSign) to what eventually became known as the P3P (Platform for Privacy Preferences).
In April 1998, Microsoft purchased Firefly, presumably because of their innovations in privacy, and their long-term goal of creating a safe marketplace for consumers' profile data which the consumer controlled. The Firefly team at Microsoft was largely responsible for the first versions of Microsoft Passport.
Microsoft shut down the website in August 1999.
The Firefly website had distinctive design and graphics. Early designs featured bright colors and a fun and eclectic look. Later redesigns reflected the company's push towards corporate customers and desire to de-emphasize the Firefly community website.
Collaborative filtering (CF) is a technique used by recommender systems. Collaborative filtering has two senses, a narrow one and a more general one.In the newer, narrower sense, collaborative filtering is a method of making automatic predictions (filtering) about the interests of a user by collecting preferences or taste information from many users (collaborating). The underlying assumption of the collaborative filtering approach is that if a person A has the same opinion as a person B on an issue, A is more likely to have B's opinion on a different issue than that of a randomly chosen person. For example, a collaborative filtering recommendation system for television tastes could make predictions about which television show a user should like given a partial list of that user's tastes (likes or dislikes). Note that these predictions are specific to the user, but use information gleaned from many users. This differs from the simpler approach of giving an average (non-specific) score for each item of interest, for example based on its number of votes.
In the more general sense, collaborative filtering is the process of filtering for information or patterns using techniques involving collaboration among multiple agents, viewpoints, data sources, etc. Applications of collaborative filtering typically involve very large data sets. Collaborative filtering methods have been applied to many different kinds of data including: sensing and monitoring data, such as in mineral exploration, environmental sensing over large areas or multiple sensors; financial data, such as financial service institutions that integrate many financial sources; or in electronic commerce and web applications where the focus is on user data, etc. The remainder of this discussion focuses on collaborative filtering for user data, although some of the methods and approaches may apply to the other major applications as well.Dave Janusko
Dave Janusko (born 8 September 1965) is an American songwriter, musician, producer, DJ, and remixer. He lives in San Francisco.