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» Do Metrics Make Recommender Algorithms
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FLAIRS
2004
13 years 9 months ago
A New Filtering Model towards an Intelligent Guide Agent
In E-learning systems, where both helpers (tutors) and learners are separated geographically, finding a reliable helper is one of the most important challenges. Although helpers c...
Mohammed Abdel Razek, Claude Frasson, Marc Kaltenb...
IR
2002
13 years 7 months ago
An Empirical Analysis of Design Choices in Neighborhood-Based Collaborative Filtering Algorithms
Collaborative filtering systems predict a user's interest in new items based on the recommendations of other people with similar interests. Instead of performing content index...
Jonathan L. Herlocker, Joseph A. Konstan, John Rie...
CIKM
2011
Springer
12 years 8 months ago
Effective retrieval of resources in folksonomies using a new tag similarity measure
Social (or folksonomic) tagging has become a very popular way to describe content within Web 2.0 websites. However, as tags are informally defined, continually changing, and ungo...
Giovanni Quattrone, Licia Capra, Pasquale De Meo, ...
SIGSOFT
2007
ACM
14 years 8 months ago
Measuring empirical computational complexity
The standard language for describing the asymptotic behavior of algorithms is theoretical computational complexity. We propose a method for describing the asymptotic behavior of p...
Simon Goldsmith, Alex Aiken, Daniel Shawcross Wilk...
SIGIR
2009
ACM
14 years 2 months ago
Temporal collaborative filtering with adaptive neighbourhoods
Recommender Systems, based on collaborative filtering (CF), aim to accurately predict user tastes, by minimising the mean error achieved on hidden test sets of user ratings, afte...
Neal Lathia, Stephen Hailes, Licia Capra