Happy Beer Time Popularity Slider: Diving into the long ta « Matt Locke on folksonomies | Main | Vimeo - tagged video » March 1, 2005 Popularity Slider: Diving into the long tail Posted by Seb Paquet The general idea of a recommender system is that it asks for a few examples of things you like and then gives you more things it thinks you might like, based on its knowledge of other people’s preferences. One problem you can often run into when using a recommender system is a bias towards popular items, which are not really that close to what you like but have the favor of many users because of their high visibility. An easy way to mitigate this is to selectively decapitate the recommendation engine’s results. I like how things like this underscore the idea that “this is popular” is not the same as “you’ll like it”. Comments (7) + TrackBacks (0) | Category: social software › Spolsky on Blog Comments: Scale matters › "The internet's output is data, but its product is freedom" › Andrew Keen: Rescuing 'Luddite' from the Luddites
Beer Info - Brews News Service plus Craft Beer and Homebrew Library Oxbow Beer Technology News - CNET News Today's NYT Strands Hints, Answers and Help for Aug. 28, #178 Malts & Houblons Automated Collaborative Filtering and Semantic Transports - draf This essay focuses on the conceptualization of the issues, comparisons of current technological developments to other historical/evolutionary processes, future of automated collaboration and its implications for economic and social development of the world, and suggestions of what we may want to pursue and avoid. Explanations of the workings of the technology and analysis of the current market are not my purpose here, although some explanations and examples may be appropriate. Please send your suggestions to sasha1@netcom.com You can find an up-to-date version of the essay at Abstract Automated Collaborative Filtering of information (ACF) is an unprecedented technology for distribution of opinions and ideas in society and facilitating contacts between people with similar interests. Premises of Automated Collaborative Filtering Information flows in the society Collaborative filtering of information Active Collaborative Filtering
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