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Which clippings match 'Recommendation Engine' keyword pg.1 of 1
04 JANUARY 2014

An introduction to recommender systems


TAGS • affinity analysisalgorithmic filtersAmazon.comautomatic predictions • collaborative filtering • collaborative filtering approach • correlationsdata matchingdata miningecho chamberfavourite things • FilmTrust • information filtering • information filtering system • information patterns • interests • Jennifer Golbeck • large • • Pandora Radiopersonal tastepersonalised suggestionsprediction • process of filtering • rating systemrecommendationrecommendation enginerecommendation platform • recommendation system • recommendation systems • recommender systems • relatednessrelationships between individualsserendipitysimilaritysimilarity machinesimilitude • trust metric • trust-based recommender systems • user datauser preferences


Simon Perkins
14 FEBRUARY 2010

Get your recommendations in Spotify

"Another improvement has been rolled out to Spotify recommendations engine Spotibot. The service, which aims to help users find music they like, but just don't know yet, has added integration.

What that means is that instead of having to put in a song or band name you like, you can just get recommendations based on your recent listening instead. You just put in your account name, or the account of anyone else for that matter, and you can generate a list of 5 to 30 songs that you're going to love. Well, maybe. ...

This is just the 'recommendations' bit of at work. It also has 'your library', 'neighborhood' and 'loved tracks' functionality that could easily be added in the same way, so keep your eyes on Spotibot over the next month or so."




Simon Perkins
12 FEBRUARY 2010

Mr. Taggy: a cross between a search engine and a recommendation engine

"MrTaggy is an experiment in web search and exploration built on top of a PARC algorithm called TagSearch. Think of MrTaggy as a cross between a search engine and a recommendation engine: it's a web browsing guide constructed from social tagging data.

Unlike most search engines, MrTaggy doesn't index the text on a web page. Instead, it leverages the knowledge contained in the tags that people add to web pages when using social bookmarking services. Tags describe both the content and context of a web page, and we use that information to deliver relevant search results.

The problem with using social tags is that they contain a lot of noise, because people often use different words to mean the same thing or the same words to mean different things. The TagSearch algorithm is part of our ongoing research to reduce the noise while amplifying the information signal from social tags."

(PARC's Augmented Social Cognition Area)



algorithmICTinformation in contextinnovationknowledge-based economymetadata • MrTaggy • PARC • recommendation enginesearchsearch enginesemanticssocial bookmarking • social tagging • social tagging data • social tags • solutiontags • TagSearch • technology • web browsing • web search


Simon Perkins

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