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Search results for: recommender systems
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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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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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An Ontology-based Contextual Pre-filtering Technique for Recommender Systems
PublicationContext-aware Recommender Systems aim to provide users with the most adequate recommendations for their current situation. However, an exact context obtained from a user could be too specific and may not have enough data for accurate rating prediction. This is known as the data sparsity problem. Moreover, often user preference representation depends on the domain or the specific recommendation approach used. Therefore, a big effort...
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An Ontology-based Contextual Pre-filtering Technique for Recommender Systems
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ACM International Conference on Recommender Systems
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Rozwój medycznego systemu komputerowego Endoscopy Recommender System
PublicationPrzedstawiono rozwój medycznego systemu komputerowego do badań endoskopowych Endoscopy Recommender System ze szczególnym zwróceniem uwagi na rozwój architektury systemu i bazy danych. Opisano wpływ ewolucji technologii i wymagań systemowych na podejście do magazynowania i zarządzania danymi pacjentów. Omówiono architekturę nowego systemu oraz metodologię wprowadzania zmian w systemie.
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Achieving High Dependability of an Endoscopy Recommender System (ERS).
PublicationZaprezentowano strategię zwiększenia wiarygodności komputerowego systemu zorientowanego na wspomaganie badań endoskopowych. zasygnalizowano podstawowe funkcje systemu (ERS) oraz podano mechanizmy rekonfiguracji sprzętowej (nadmiarowość komputerów) oraz bazodanowej (nadmierność dokumentów badań). Zbadano wpływ tych mechanizmów na wydajność, wiarygodność oraz bezpieczeństwo tego systemu.
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Listening to Live Music: Life beyond Music Recommendation Systems
PublicationThis paper presents first a short review on music recommendation systems based on social collaborative filtering. A dictionary of terms related to music recommendation systems, such as music information retrieval (MIR), Query-by-Example (QBE), Query-by-Category (QBC), music content, music annotating, music tagging, bridging the semantic gap in music domain, etc. is introduced. Bases of music recommender systems are shortly presented,...
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Multi-Criteria Knowledge-Based Recommender System for Decision Support in Complex Business Processes
PublicationIn this paper, we present a concept of a multi-criteria knowledge-based Recommender System (RS) designed to provide decision support in complex business process (BP) scenarios. The developed approach is based on the knowledge aspects of Stylistic Patterns, Business Sentiment and Decision-Making Logic extracted from the BP unstructured texts. This knowledge serves as an input for a multi-criteria RS algorithm. The output is prediction...
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Multidimensional legacy aspects of modernizing web based systems
PublicationPublikacja porusza zagadnienia technik modernizacji tzw. legacy systems mających zastosowanie w cyklach życia oprogramowania. Przedmiotem dyskusji jest także studium przypadku Endoscopy Recommender System. Ponadto rozważany jest wpłw zmian wymagań, platform, standardów oraz strategii rozwoju oprogramowania na status legacy aplikacji webowych.
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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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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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Serendipitous Recommendations Through Ontology-Based Contextual Pre-filtering
PublicationContext-aware Recommender Systems aim to provide users with better recommendations for their current situation. Although evaluations of recommender systems often focus on accuracy, it is not the only important aspect. Often recommendations are overspecialized, i.e. all of the same kind. To deal with this problem, other properties can be considered, such as serendipity. In this paper, we study how an ontology-based and context-aware...
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Things You Might Not Know about the k-Nearest Neighbors Algorithm
PublicationRecommender Systems aim at suggesting potentially interesting items to a user. The most common kind of Recommender Systems is Collaborative Filtering which follows an intuition that users who liked the same things in the past, are more likely to be interested in the same things in the future. One of Collaborative Filtering methods is the k Nearest Neighbors algorithm which finds k users who are the most similar to an active user...
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Document transformations for data processing in information systems
PublicationAtrykuł przedstawia podejście do automatyzacji transformacjidokumentów użytkownika bazujące na technologii XML. W artykuleprzedstawiony został system Endoscopy Recommender System.ERS wykorzystuje dedykowane transformacje XML Schema do Java, Java dodokumentów XML. Dzięki tym transformacjom procesy pobierania iprzechowywania danych zostały w pełni zautomatyzowane.Zaimplementowane podejście XML data binding umożliwia walidacjępodstawowych...
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Krzysztof Goczyła prof. dr hab. inż.
PeopleKrzysztof Goczyła, full professor of Gdańsk University of Technology, computer scientist, a specialist in software engineering, knowledge engineering and databases. He graduated from the Faculty of Electronics Technical University of Gdansk in 1976 with a degree in electronic engineering, specializing in automation. Since then he has been working at Gdańsk University of Technology. In 1982 he obtained a doctorate in computer science...
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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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Multi-domain and Context-Aware Recommendations Using Contextual Ontological User Profile
PublicationRecommender Systems (RS) became popular tools in many Web services like Netflix, Amazon, or YouTube, because they help a~user to avoid an information overload problem. One of the types of RS are Context-Aware RS (CARS) which exploit contextual information to provide more adequate recommendations. Cross-Domain RS (CDRS) were created as a response to the data sparsity problem which occurs when only few users can provide reviews or...
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Aleksandra Karpus dr inż.
PeopleAleksandra Karpus jest absolwentką Matematyki Stosowanej na Wydziale Fizyki Technicznej i Matematyki Stosowanej oraz Informatyki na Wydziale Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej. W latach 2011-2014 pracowała z danymi w przemyśle, wykorzystując bazy danych Oracle. Od 2014 roku jest zawodowo związana z Politechniką Gdańską, obecnie jest zatrudniona na stanowisku adiunkta naukowo-dydaktycznego w Katedrze...
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Identification of category associations using a multilabel classifier
PublicationDescription of the data using categories allows one to describe it on a higher abstraction level. In this way, we can operate on aggregated groups of the information, allowing one to see relationships that do not appear explicit when we analyze the individual objects separately. In this paper we present automatic identification of the associations between categories used for organization of the textual data. As experimental data...
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Multimedialna karta pacjenta
PublicationPrzedstawiono założenia i rozwiązania systemu komputerowego wprowadzającego dane multimedialne do historii choroby pacjenta. Zdefiniowano pojęcie ''Multimedialnej karty pacjenta''. Omówiono rozwój architektury i kompnentów systemu Endoscopy Recommender System. Przedstawiono proces oraz metodologię wdrożenia Multimedialnej Karty Pacjenta.
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Deep learning for recommending subscription-limited documents
PublicationDocuments recommendation for a commercial, subscription-based online platform is important due to the difficulty in navigation through a large volume and diversity of content available to clients. However, this is also a challenging task due to the number of new documents added every day and decreasing relevance of older contents. To solve this problem, we propose deep neural network architecture that combines autoencoder with...
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The parallel environment for endoscopic image analysis
PublicationThe jPVM-oriented environment to support high performance computing required for the Endoscopy Recommender System (ERS) is defined. SPMD model of image matching is considered and its two implementations are proposed: Lexicographical Searching Algorithm (LSA) and Gradient Serching Algorithm (GSA). Three classes of experiments are considered and the relative degree of similarity and execution time of each algorithm are analysed....
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Tworzenie i wykorzystanie bazy wzorców zmian chorobowych
PublicationPrzedstawiono bazy danych zbudowane na potrzeby systemu wspomagania badan medycznych oraz aplikacje je wykorzystujace. Szczególna uwaga poswiecona została bazie danych wzorców medycznych, której rozmiar czyni ja jedna z wiekszych baz stosowanych w dziedzinie. Artykuł zawiera obszerny przeglad zgromadzonych w bazie przypadków chorobowych, zestawionych według rodzajów schorzen oraz według miejsca wystapienia schorzenia. Konstrukcja...
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Andrzej Sobecki dr inż.
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Systematic Literature Review on Click Through Rate Prediction
PublicationThe ability to anticipate whether a user will click on an item is one of the most crucial aspects of operating an e-commerce business, and clickthrough rate prediction is an attempt to provide an answer to this question. Beginning with the simplest multilayer perceptrons and progressing to the most sophisticated attention networks, researchers employ a variety of methods to solve this issue. In this paper, we present the findings...
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Karolina Selwon mgr inż.
People