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Outputs (156)

Social learning in repeated cooperation games in uncertain environments (2018)
Journal Article
Andras, P. (2018). Social learning in repeated cooperation games in uncertain environments. Cognitive Systems Research, 51, 24-39. https://doi.org/10.1016/j.cogsys.2018.04.013

Cooperation and social learning are fundamental mechanisms that maintain social organisation among animals and humans. Social institutions can be conceptualised abstractly as cooperation games with social learning. In some cases potential cooperation... Read More about Social learning in repeated cooperation games in uncertain environments.

On the Fractal Nature of Local Optima Networks (2018)
Presentation / Conference Contribution
Thomson, S. L., Verel, S., Ochoa, G., Veerapen, N., & McMenemy, P. (2018, April). On the Fractal Nature of Local Optima Networks. Presented at 18th European Conference: EvoCOP 2018, Parma, Italy

A Local Optima Network represents fitness landscape connectivity within the space of local optima as a mathematical graph. In certain other complex networks or graphs there have been recent observations made about inherent self-similarity. An object... Read More about On the Fractal Nature of Local Optima Networks.

The effect of landscape funnels in QAPLIB instances (2017)
Presentation / Conference Contribution
Thomson, S. L., Ochoa, G., Daolio, F., & Veerapen, N. (2017, July). The effect of landscape funnels in QAPLIB instances. Presented at GECCO '17: Genetic and Evolutionary Computation Conference, Berlin, Germany

The effectiveness of common metaheuristics on combinatorial optimisation problems can be limited by certain characteristics of the fitness landscape. We use the local optima network model to compress the 'inherent structure' of a problem space into a... Read More about The effect of landscape funnels in QAPLIB instances.

Comparing communities of optima with funnels in combinatorial fitness landscapes (2017)
Presentation / Conference Contribution
Thomson, S. L., Daolio, F., & Ochoa, G. (2017, July). Comparing communities of optima with funnels in combinatorial fitness landscapes. Presented at GECCO '17: Genetic and Evolutionary Computation Conference, Berlin, Germany

The existence of sub-optimal funnels in combinatorial fitness landscapes has been linked to search difficulty. The exact nature of these structures --- and how commonly they appear --- is not yet fully understood. Improving our understanding of funne... Read More about Comparing communities of optima with funnels in combinatorial fitness landscapes.

Evolutionary computing in recommender systems: a review of recent research (2016)
Journal Article
Horváth, T., & de Carvalho, A. C. P. L. F. (2017). Evolutionary computing in recommender systems: a review of recent research. Natural Computing, 16(3), 441-462. https://doi.org/10.1007/s11047-016-9540-y

One of the main current applications of intelligent systems is recommender systems (RS). RS can help users to find relevant items in huge information spaces in a personalized way. Several techniques have been investigated for the development of RS. O... Read More about Evolutionary computing in recommender systems: a review of recent research.

Leveraging the Cloud for Large-Scale Software Testing: A Case Study ‑ Google Chrome on Amazon (2014)
Book Chapter
Pakhira, A., & Andras, P. (2014). Leveraging the Cloud for Large-Scale Software Testing: A Case Study ‑ Google Chrome on Amazon. In Cloud Technology: Concepts, Methodologies, Tools, and Applications. IGI Global. https://doi.org/10.4018/978-1-4666-6539-2.ch055

Testing is a critical phase in the software life-cycle. While small-scale component-wise testing is done routinely as part of development and maintenance of large-scale software, the system level testing of the whole software is much more problematic... Read More about Leveraging the Cloud for Large-Scale Software Testing: A Case Study ‑ Google Chrome on Amazon.

Ranking Formal Concepts by Utilizing Matrix Factorization (2014)
Presentation / Conference Contribution
Pisková, L., Horvath, T., & Krajči, S. Ranking Formal Concepts by Utilizing Matrix Factorization. Presented at 12th International Conference on Formal Concept Analysis, Cluj-Napoca, Romania

Formal Concept Analysis often produce huge number of formal concepts even for small input data. Such a large amount of formal concepts, which is intractable to analyze for humans, calls for a kind of
a ranking of formal concepts according to their i... Read More about Ranking Formal Concepts by Utilizing Matrix Factorization.

Buried pipe localization using an iterative geometric clustering on GPR data (2013)
Journal Article
Janning, R., Busche, A., Horváth, T., & Schmidt-Thieme, L. (2014). Buried pipe localization using an iterative geometric clustering on GPR data. Artificial Intelligence Review, 42(3), 403-425. https://doi.org/10.1007/s10462-013-9410-2

Ground penetrating radar is a non-destructive method to scan the shallow subsurface for detecting buried objects like pipes, cables, ducts and sewers. Such buried objects cause hyperbola shaped reflections in the radargram images achieved by GPR. Ori... Read More about Buried pipe localization using an iterative geometric clustering on GPR data.

Factorization Techniques for Predicting Student Performance (2012)
Book Chapter
Thai-Nghe, N., Drumond, L., Horváth, T., Krohn-Grimberghe, A., Nanopoulos, A., & Schmidt-Thieme, L. (2012). Factorization Techniques for Predicting Student Performance. In O. C. Santos, & J. G. Boticario (Eds.), Educational Recommender Systems and Technologies: Practices and Challenges (129-153). IGI Global. https://doi.org/10.4018/978-1-61350-489-5.ch006

Recommender systems are widely used in many areas, especially in e-commerce. Recently, they are also applied in e-learning for recommending learning objects (e.g. papers) to students. This chapter introduces state-of-the-art recommender system techni... Read More about Factorization Techniques for Predicting Student Performance.

GRAMOFON: General model-selection framework based on networks (2011)
Journal Article
Buza, K., Nanopoulos, A., Horváth, T., & Schmidt-Thieme, L. (2012). GRAMOFON: General model-selection framework based on networks. Neurocomputing, 75(1), 163-170. https://doi.org/10.1016/j.neucom.2011.02.026

Ensembles constitute one of the most prominent class of hybrid prediction models. One basically assumes that different models compensate each other's errors if one combines them in an appropriate way. Often, a large number of various prediction model... Read More about GRAMOFON: General model-selection framework based on networks.

User Preference Web Search -- Experiments with a System Connecting Web and User (2009)
Journal Article
Gurský, P., Horvath, T., Jirásek, J., Krajči, S., Novotny, R., Pribolová, J., Vaneková, V., & Vojtáš, P. (2009). User Preference Web Search -- Experiments with a System Connecting Web and User. Computing and Informatics, 28(4), 1001-1033

We present models, methods, implementations and experiments with a system enabling personalized web search for many users with different preferences. The system consists of a web information extraction part, a text search engine, a middleware support... Read More about User Preference Web Search -- Experiments with a System Connecting Web and User.

A Model of User Preference Learning for Content-Based Recommender Systems (2009)
Journal Article
Horvath, T. (2009). A Model of User Preference Learning for Content-Based Recommender Systems. Computing and Informatics, 28(4), 1001-1029

This paper focuses to a formal model of user preference learning for
content-based recommender systems. First, some fundamental and special requirements to user preference learning are identified and proposed. Three learning tasks are introduced as... Read More about A Model of User Preference Learning for Content-Based Recommender Systems.

Knowledge Processing for Web Search – An Integrated Model and Experiments (2008)
Presentation / Conference Contribution
Gurský, P., Horvath, T., Jirásek, J., Novotny, R., Pribolová, J., Vaneková, V., & Vojtáš, P. Knowledge Processing for Web Search – An Integrated Model and Experiments. Presented at Symposium on Intelligent and Distributed Computing IDC, Craiova, Romania

We propose a model of a middleware system enabling personalized web
search for users with different preferences. We integrate both inductive and deductive tasks to find user preferences and consequently best objects. The model is based on modeling p... Read More about Knowledge Processing for Web Search – An Integrated Model and Experiments.

Integration of two fuzzy data mining methods (2004)
Journal Article
Horvath, T., & Krajči, S. (2004). Integration of two fuzzy data mining methods. Neural Network World, 14(5), 391-402

The cluster analysis and the formal concept analysis are both used to identify significiant groups of similar objects. Rice & Siff's algorithm for the clustering joins these two methods in the case where the values of an object-attribute model are 1... Read More about Integration of two fuzzy data mining methods.

An ILP model for a monotone graded classification problem (2004)
Presentation / Conference Contribution
Vojtáš, P., Horvath, T., Krajči, S., & Lencses, R. An ILP model for a monotone graded classification problem. Presented at Znalosti 2003, Ostrava, Czech Republic

Motivation for this paper are classification problems in which data can not be clearly divided into positive and negative examples, especially data in which there is a monotone hierarchy (degree, preference) of more or less positive (negative) exampl... Read More about An ILP model for a monotone graded classification problem.