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Search results for: CONDITIONAL PREFERENCES
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Rating Prediction with Contextual Conditional Preferences
PublicationExploiting contextual information is considered a good solution to improve the quality of recommendations, aiming at suggesting more relevant items for a specific context. On the other hand, recommender systems research still strive for solving the cold-start problem, namely where not enough information about users and their ratings is available. In this paper we propose a new rating prediction algorithm to face the cold-start...
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Top k Recommendations using Contextual Conditional Preferences Model
PublicationRecommender systems are software tools and techniques which aim at suggesting to users items they might be interested in. Context-aware recommender systems are a particular category of recommender systems which exploit contextual information to provide more adequate recommendations. However, recommendation engines still suffer from the cold-start problem, namely where not enough information about users and their ratings is available....
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Using contextual conditional preferences for recommendation taska: a case study in the movie domain
PublicationRecommendation engines aim to propose users items they are interested in by looking at the user interaction with a system. However, individual interests may be drastically influenced by the context in which decisions are taken. We present an attempt to model user interests via a set of contextual conditional preferences. We show that usage of proposed preferences gives reasonable values of the accuracy and the precision even when...
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Improving Re-rankCCP with Rules Quality Measures
PublicationRecommender Systems are software tools and techniques which aim at suggesting new items that may possibly be of interest to a user. Context-Aware Recommender Systems exploit contextual information to provide more adequate recommendations. In this paper we described a modification of an existing contextual post-filtering algorithm which uses rules-like user representation called Contextual Conditional Preferences. We extended the...
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Context-aware User Modelling and Generation of Recommendations in Recommender Systems
PublicationRecommender systems are software tools and techniques which aim at suggesting new items that may be of interest to a user. This dissertation is focused on four problems in recommender systems domain. The first one is context-awareness, i.e. how to obtain relevant contextual information, how to model user preferences in a context and use them to make predictions. The second one is multi-domain recommendation, which aim at suggesting...
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Investor confidence and high financial literacy jointly shape investments in risky assets
PublicationHouseholds consistently invest less in equities and bonds than predicted by economic theory. We explain this from a behavioral economics perspective and distributional analysis using rich US survey microdata. We find that higher investor self-confidence in her financial abilities and financial literacy jointly increase the probability of investing in equities. Conditional on participation, confidence in the macroeconomy additionally...
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Investor confidence and high financial literacy jointly shape investments in risky assets
PublicationHouseholds consistently invest less in equities and bonds than predicted by economic theory. We explain this from a behavioral economics perspective and distributional analysis using rich US survey microdata. We find that higher investor self-confidence in her financial abilities and financial literacy jointly increase the probability of investing in equities. Conditional on participation, confidence in the macroeconomy additionally...