Wyszukiwarka
dr inż. Aleksandra Karpus
Zatrudnienie
- Adiunkt w Katedra Inżynierii Oprogramowania
Publikacje
Filtry
wszystkich: 17
Katalog Publikacji
Rok 2023
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Databases and Information Systems: Contributions from ADBIS 2023 Workshops and Doctoral Consortium
Publikacja
Rok 2022
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Automatic Emotion Recognition in Children with Autism: A Systematic Literature Review
PublikacjaThe automatic emotion recognition domain brings new methods and technologies that might be used to enhance therapy of children with autism. The paper aims at the exploration of methods and tools used to recognize emotions in children. It presents a literature review study that was performed using a systematic approach and PRISMA methodology for reporting quantitative and qualitative results. Diverse observation channels and modalities...
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Improving Re-rankCCP with Rules Quality Measures
PublikacjaRecommender 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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Multi-domain and Context-Aware Recommendations Using Contextual Ontological User Profile
PublikacjaRecommender 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...
Rok 2021
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MobileNet family tailored for Raspberry Pi
PublikacjaWith the advances in systems-on-a-chip technologies, there is a growing demand to deploy intelligent vision systems on low-cost microcomputers. To address this challenge, much of the recent research has focused on reducing the model size and computational complexity of contemporary convolutional neural networks (CNNs). The state-of-the-art lightweight CNN is MobileNetV3. However, it was designed to achieve a good trade-off between...
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Ontological Model for Contextual Data Defining Time Series for Emotion Recognition and Analysis
PublikacjaOne of the major challenges facing the field of Affective Computing is the reusability of datasets. Existing affective-related datasets are not consistent with each other, they store a variety of information in different forms, different formats, and the terms used to describe them are not unified. This paper proposes a new ontology, ROAD, as a solution to this problem, by formally describing the datasets and unifying the terms...
Rok 2019
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Things You Might Not Know about the k-Nearest Neighbors Algorithm
PublikacjaRecommender 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...
Rok 2018
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Context-aware User Modelling and Generation of Recommendations in Recommender Systems
PublikacjaRecommender 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...
Rok 2017
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Serendipitous Recommendations Through Ontology-Based Contextual Pre-filtering
PublikacjaContext-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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Top k Recommendations using Contextual Conditional Preferences Model
PublikacjaRecommender 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....
Rok 2016
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A CONTEXT IN RECOMMENDER SYSTEMS
PublikacjaRecommender 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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An Ontology-based Contextual Pre-filtering Technique for Recommender Systems
PublikacjaContext-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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Rating Prediction with Contextual Conditional Preferences
PublikacjaExploiting 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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RECSYS CHALLENGE 2015: a BUY EVENT PREDICTION IN THE E-COMMERCE DOMAIN
PublikacjaIn this paper we present our approach to RecSys Challenge 2015. Given a set of e-commerce events, the task is to predict whether a user will buy something in the current session and, if yes, which of the item will be bought. We show that the data preparation and enrichment are very important in finding the solution for the challenge and that simple ideas and intuitions could lead to satisfactory results. We also show that simple...
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Using contextual conditional preferences for recommendation taska: a case study in the movie domain
PublikacjaRecommendation 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...
Rok 2014
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Jakość w inżynierii ontologii
PublikacjaW artykule podjęto rozważania na temat tego, czy metodologie w inżynierii ontologii są potrzebne i jak tworzyć ontologie wysokiej jakości. Dokonano przeglądu istniejących metod inżynierii ontologii, jakimi są OntoClean, Methontology i NeOn. Przedstawiono praktyczne wykorzystanie tych metod przy tworzeniu prostej ontologii opisującej świat uczelni wyższych. Podjęto próbę porównania i oceny wspomnianych metodologii w kontekście budowy...
Rok 2013
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PROBLEMY OCENY JAKOŚCI ONTOLOGII
PublikacjaW artykule podjęto rozważania na temat tego, czym jest jakość ontologii, jak zmierzyć jakość istniejących ontologii i jak tworzyć ontologie wysokiej jakości. Dokonano przeglądu istniejących metryk ontologii, które mogą posłużyć do oceny jakości ontologii. Przedstawiono problem zapewniania i oceny jakości ontologii modularnych jako ważny problem badawczy w obliczu pojawiania się skom¬plikowanych, trudnych do użycia i modyfikacji...
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