Online Collaborative Filtering on Graphs
نویسندگان
چکیده
منابع مشابه
Online Collaborative Filtering on Graphs
A common phenomena in modern recommendation systems is the use of feedback from one user to infer the ‘value’ of an item to other users. This results in an exploration vs. exploitation trade-off, in which items of possibly low value have to be presented to users in order to ascertain their value. Existing approaches to solving this problem focus on the case where the number of items are small, ...
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Collaborative Filtering (CF) is one of the most successful learning techniques in building real-world recommender systems. Traditional CF algorithms are often based on batch machine learning methods which suffer from several critical drawbacks, e.g., extremely expensive model retraining cost whenever new samples arrive, unable to capture the latest change of user preferences over time, and high...
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We study two online clustering methods for collaborative filtering. In the first method, we assume that each user is equally likely to belong to one of m clusters of users and that the user’s rating for each item is generated randomly according to a distribution that depends on the item and the cluster that the user belongs to. In the second method, we assume that each user is equally likely to...
متن کاملOnline Queries for Collaborative Filtering
Collaborative filtering allows the preferences of multiple users to be pooled in a principled way in order to make recommendations about products, services or information unseen by a specific user. We consider here the problem of online and interactive collaborative filtering: given the current ratings and recommendations associated with a user, what queries (new ratings) would most improve the...
متن کاملUncertain Graphs meet Collaborative Filtering
Collaborative ltering (CF) aims at predicting the user interest for a given item. In CF systems a set of users ratings is used to predict the rating of a given user on a given item using the ratings of a set of users who have already rated the item and whose preferences are similar to those of the user. In this paper we propose to use a framework based on uncertain graphs in order to deal with ...
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ژورنال
عنوان ژورنال: Operations Research
سال: 2016
ISSN: 0030-364X,1526-5463
DOI: 10.1287/opre.2016.1508