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prof. dr hab. inż. Krzysztof Goczyła
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- Professor at Department of Software Engineering
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total: 109
Catalog Publications
Year 2024
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Exploring Relationships Between Data in Enterprise Information Systems by Analysis of Log Contents
PublicationEnterprise systems are inherently complex and maintaining their full, up-to-date overview poses a serious challenge to the enterprise architects’ teams. This problem encourages the search for automated means of discovering knowledge about such systems. An important aspect of this knowledge is understanding the data that are processed by applications and their relationships. In our previous work, we used application logs of an enterprise...
Year 2023
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Discovering relationships between data in an enterprise information system using log analysis
PublicationEnterprise systems are inherently complex and maintaining their full, up-to-date overview poses a serious challenge to the enterprise architects’ teams. This problem encourages the search for automated means of discovering knowledge about such systems. An important aspect of this knowledge is understanding the data that are processed by applications and their relationships. In our previous work, we used application logs of an enterprise...
Year 2022
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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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Landscape of Automated Log Analysis: A Systematic Literature Review and Mapping Study
PublicationLogging is a common practice in software engineering to provide insights into working systems. The main uses of log files have always been failure identification and root cause analysis. In recent years, novel applications of logging have emerged that benefit from automated analysis of log files, for example, real-time monitoring of system health, understanding users’ behavior, and extracting domain knowledge. Although nearly every...
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Discovering interactions between applications with log analysis
PublicationApplication logs record the behavior of a system during its runtime and their analysis can provide useful information. In this article, we propose a method of automated log analysis to discover interactions taking place between applications in an enterprise. We believe that such an automated approach can greatly support enterprise architects in building an up-to-date view of a governed system in a modern, fast-paced development...
Year 2020
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Exploring application relationships within enterprise system by matching messages in enterprise log
PublicationWith data becoming their key asset, large enterprises require data governance processes to maintain its quality. Because a large portion of business value in enterprise systems is usually delivered by legacy applications without proper documentation, there is a need for a better understanding of these applications and the data produced by them. In this paper, we present an approach to collecting insights into the data managed by...
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BIG PROBLEMS WITH BIG DATA
PublicationThe article presents an overview of the most important issues related to the phenomenon called big data. The characteristics of big data concerning the data itself and the data sources are presented. Then, the big data life cycle concept is formulated. The next sections focus on two big data technologies: MapReduce for big data processing and NoSQL databases for big data storage.
Year 2019
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Artificial intelligence for software development — the present and the challenges for the future
PublicationSince the time when first CASE (Computer-Aided Software Engineering) methods and tools were developed, little has been done in the area of automated creation of code. CASE tools support a software engineer in creation the system structure, in defining interfaces and relationships between software modules and, after the code has been written, in performing testing tasks on different levels of detail. Writing code is still the task...
Year 2018
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Sztuczna inteligencja - oksymoron czy oczywistość?
PublicationW artykule przedstawiono historię powstania i rozwoju sztucznej inteligencji, jej główne obszary badawcze i perspektywy. Szczególną uwagę poświęcono uczeniu maszynowemu jako głównemu obszarowi badań naukowych. Sformułowano i skomentowano hipotezy dotyczące perspektyw sztucznej inteligencji.
Year 2017
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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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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...
Year 2016
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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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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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An Ontology-based Contextual Pre-filtering Technique for Recommender Systems
Publication -
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...
Year 2014
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Reasoning with Projection in Multimodular Description Logics Knowledge Bases
PublicationWe present an approach to reasoning with projection, i.e. reasoning in which it is possible to focus on a selected part of knowledge (by neglecting some non-interesting fragments). Projection is most useful for modular knowledge bases in which only parts of knowledge have to be exchanged or imported to other modules. In this paper we present an optimized method of reasoning over results of projection. The tests indicate that the...
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Contextualizing a Knowledge Base by Approximation – A Case Study
PublicationModular knowledge bases give their users opportunity to store and access knowledge at different levels of generality. In this paper we present how to organize a modular knowledge bases organized into contexts in which a user can express their knowledge in much simplified way, yet without losing its precision. The work is centered around the notion of approximation - i.e. reducing the arity of predicates used. The presentation is...
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Big Data i 5V – nowe wyzwania w świecie danych (Big Data and 5V – New Challenges in the World of Data)
PublicationRodzaje danych, składające się na zbiory typu Big Data, to m.in. dane generowane przez użytkowników portali internetowych, dane opisujące transakcje dokonywane poprzez Internet, dane naukowe (biologiczne, astronomiczne, pomiary fizyczne itp.), dane generowane przez roboty w wyniku automatycznego przeszukiwania przez nie Internetu (Web mining, Web crawling), dane grafowe obrazujące powiązania pomiędzy stronami WWW itd. Zazwyczaj,...
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An Analysis of Contextual Aspects of Conceptualization: A Case Study and Prospects
PublicationIn this chapter we present a new approach to development of modularized knowledge bases. We argue that modularization should start from the very beginning of modeling, i.e. from the conceptualization stage. To make this feasible, we propose to exploit a context-oriented, semantic approach to modularization. This approach is based on the Structural Interpretation Model (SIM) presented earlier elsewhere. In the first part of thischapter...
Year 2013
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Theoretical and Architectural Framework for Contextual Knowledge Bases
PublicationThe paper presents the approach aimed at building modularized knowledge bases in a systematic, context-aware way. The paper focuses on logical modeling of such knowledge bases, including an underlying SIM metamodel. The architecture of a comprehensive set of tools for knowledge-base systems engineering is presented. The tools enable an engineer to design, create and edit a knowledge base schema according to a novel context approach...
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