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Use of the AHP Method for Preference Determination in Yacht Design
PublicationA sailing yacht is a human-centred product, the design of which revolves primarily around the wants and desires of the future owner. In most cases, these preferences are not measurable, such as a personal aesthetic feeling, or a need for comfort, speed, safety etc. The aims of this paper are to demonstrate that these preferences can be classified and represented numerically, and to show that they are correlated with the type...
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Use of the AHP Method for Preference Determination in Yacht Design
PublicationA sailing yacht is a human-centred product, the design of which revolves primarily around the wants and desires of the future owner. In most cases, these preferences are not measurable, such as a personal aesthetic feeling, or a need for comfort, speed, safety etc. The aims of this paper are to demonstrate that these preferences can be classified and represented numerically, and to show that they are correlated with the type of...
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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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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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Fitting the mobile device characteristics to the user's hearing preferences
PublicationA method for fitting the mobile computer audio characteristics to the user's hearing preferences is proposed. The process consists of two stages: calibration and dynamics processing. During the calibration phase the user performs a loudness scaling test giving their response regarding the perceived loudness. The dynamics processing made on above basis sets the loudness to the most comfortable level. The processing accounts both...
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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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User experience and user interface (UX/UI) design of Greencoin mobile application.
PublicationThe aim of the Greencoin mobile application is to encourage its users to change their behavior and to act pro-ecologically. The pilot version of the application will operate within the city of Gdańsk. To keep the app’s user base as large as possible, the graphical user interface should be attractive to the broadest possible audience, and the application itself should be easy and fun to use. This work is a continuation of studies...
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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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A CONTEXT IN RECOMMENDER SYSTEMS
PublicationRecommender systems aim to propose potentially interesting items to a user based on his preferences or previous interaction with the system. In the last decade, researcher found out that known recommendation techniques are not sufficient to predict user decisions. It has been noticed that user preferences strongly depend on the context in which he currently is. This raises new challenges for the researchers such as how to obtain...
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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...