A new approach to the matrix conditionality and the solvability of the linear systems of equations is presented. It is based on the application of the geometric algebra with the projective space representation using homogeneous coordinates representation.

This contribution describes new useful geometric transformations using the tensor product. The geometric transformations are used widely in many applications, especially in CAD/CAM systems, systems for Civil Engineering, computer graphics, virtual and augmented reality, etc. The basic geometric transf...

We present our system for measuring the lexical semantic change between corpora pairs, developed for the RuShiftEval competition. We measure semantic changes in a list of test words between three different corpora (for each pair), pre-Soviet, Soviet, and post-Soviet, each from a differe...

This paper deals with cross-lingual sentiment analysis in Czech, English and French languages. We perform zero-shot cross-lingual classification using five linear transformations combined with LSTM and CNN based classifiers. We compare the performance of the individual transformations, and in addition...

This paper describes the experimental evaluation of several attribution methods on two NLP tasks: Sentiment analysis and multi-label document classification. Our motivation is to find the best method to use with Transformers to interpret model decisions. For this purpose, we introduce two&#x...

The modular addition is used as a non-linear operation in ARX ciphers because it achieves the requirement of introducing non-linearity in a cryptographic primitive while only taking one clock cycle to execute on most modern archi- tectures. This makes ARX ciphers espe...

Semantic alignment of application software components’ ontologies represents a great interest in vehicle application domains that manipulate heterogeneous overlapping knowledge application frameworks. The most daunting impediment to their cross-enterprise collaboration is semantic interoperability. Aligning the interface...

This paper describes in details an innovative technique of injection of a global (or generally largescale) quality measure into a deep neural network (DNN) in order to compensate for the tendency of DNNs to found the resulting classification virtually from a superposition of local&...

The global RBFs lead to an ill-conditioned system of linear equations, in general. This contribution analyzes conditionality of the Gauss and the Thin Plate Spline (TPS) functions. Experiments made proved dependency of the shape parameter and number of points, which can be described...

Interpolation and approximation methods are widely used in many areas. They can be divided to methods based on meshing (tessellation) of the data domain and to meshless (meshfree) methods, which do not require the domain tessellation of scattered data. Scattered n-dimensional data radia...

In this paper, we present coreference resolution experiments with a newly created multi-lingual corpus CorefUD (Nedoluzhko et al.,2021). We focus on the following languages: Czech, Russian, Polish, German, Spanish, and Catalan. In addition to monolingual experiments, we combine the training data&...

Software systems of all kinds tend to be complex, easily comprising hundreds of components of various types and many more interconnections. Understanding of their internal structure through appropriate visualization is, therefore, a challenging task, especially when hierarchical decomposition is not&#...

When service-based applications are used in systems where context varies in time or location (mobile, adaptive systems), clients may need to switch service providers for various reasons like temporary outage or geographical relocation. To prevent negative impacts on overall functionality, both&#x...

A common need in software project management and process improvement is to detect the occurrence of project mishaps and management mistakes, if possible based on data available from project management and development tools. Process anti-patterns describe such re-occurring problems in textual ...

This competition consists in solving several challenges which arise during the processing of images of historical maps. In the Western world, the rapid development of geodesy and cartography from the 18th century resulted in massive production of topographic maps at various scales. City...

Nowadays, named entity recognition (NER) achieved excellent results on the standard corpora. However, big issues are emerging with a need for an application in a specific domain, because it requires a suitable annotated corpus with adapted NE tag-set. This is particularly evident in...

Semantic textual similarity (STS) systems estimate the degree of the meaning similarity between two sentences. Cross-lingual STS systems estimate the degree of the meaning similarity between two sentences, each in a different language. State-of-the-art algorithms usually employ a strongly supervised,&...

This paper describes Slav-NER: the 3rd Multilingual Named Entity Challenge in Slavic languages. The tasks involve recognizing mentions of named entities in Web documents, normalization of the names, and cross-lingual linking. The Challenge covers six languages and five entity types, and is&#...

In this paper, we aim at improving Czech sentiment with transformer-based models and their multilingual versions. More concretely, we study the task of polarity detection for the Czech language on three sentiment polarity datasets. We fine-tune and perform experiments with five multilingual&...

This paper describes the training process of the first Czech monolingual language representation models based on BERT and ALBERT architectures. We pre-train our models on more than 340K of sentences, which is 50 times more than multilingual models that include Czech data. We outper...