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Conformal prediction is a relatively recent approach for quantifying the uncertainty in classification problems. It can provide reliable measures of confidence for predicting class labels of unclassified patterns. This framework is applicable to classification problems but the implementation of conformal prediction for classification depends on the classification algorithm at hand. In literature,...
The problem of building Recommender Systems has attracted considerable attention in recent years, but most recommender systems are designed for recommending items for individuals. In this paper we develop a content based group recommender system that can recommend TV shows to a group of users. We propose a method that uses decision list rule learner (DLRL) based on Ripper to learn the rule base from...
Personalized recommender systems are usually designed to provide recommendations adapted to the preferences of a single user. Group recommender systems on the other hand suggest items to a group by combining individual models into a group model. This group model allows to merge the preferences of the individual members of a group and thereby derive a group preference for each item by using different...
Recommender Systems, these days, are no longer personal recommender systems, rather they are group recommender systems which list out recommendations for a group of users. Also, they are an integral part of today's web sites (mainly shopping, search engine etc.) who want to keep track of their users' preferences. Although we cannot build a recommender system for every individual, we can build a recommender...
Recommender systems are designed in such a way that they sort through massive amounts of data so as to help users in finding their preferred items. Currently much research on recommender systems focus on improving the prediction or classification accuracy of the respective algorithms while behavioral aspects are often overlooked. In this paper we focus on a particular behavioral property called monotonicity...
Recommender systems are the software or technical tools that help user to find out items/things according to his/her preferences from a wide range of items/things. For example, selecting a movie from a large database of movies from on-line or selecting a song of his/her own kind from a large number of songs available in the internet and much more. In order to generate recommendations for the users...
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