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...

The paper introduces a new randomized sampling-based method of motion planning suitable for the problem of narrow passages. The proposed method was inspired by the method of exit points for cavities in protein models and is based on the Rapidly Exploring Random Tree (RRT). Unl...

A natural method to evaluate the effectiveness of a testing technique is to measure the defect detection rate when applying the created test cases. Here, real or artificial software defects can be injected into the source code of software. For a more extensive evaluation, inje...

This paper summarizes findings related to the problematics of glottis detection in video sequences obtained by medical examination of vocal cords by high speed videolaryngoscopy (HSV). The glottis detection is based on cluster analysis method K-means which complements the existing set of...

Brief description of a method based on computing correlation between parameters for vocal cords recorded by high speed video camera. This method gives us possibility to analyze vocal cords kinematics and tries to evaluate specific vocal cords based on statistical data.

In this paper, two efficient communication protocols for distributed road traffic simulation, which we developed during our previous research, are compared. These protocols – the Long Step (LS) protocol and the Long Step Binary (LSB) protocol – reduce the inter-process communication using&#x...

In this paper, we describe our method for detection of lexical semantic change, i.e., word sense changes over time. We examine semantic differences between specific words in two corpora,chosen from different time periods, for English, German, Latin, and Swedish. Our method was created&#...

This paper deals with multi-lingual dialogue act (DA) recognition. The proposed approaches are based on deep neural networks and use word2vec embeddings for word representation. Two multi-lingual models are proposed for this task. The first approach uses one general model trained on the...

Over the past couple of years, machine learning methods—especially the outlier detection ones—have anchored in the cybersecurity field to detect network-based anomalies rooted in novel attack patterns. However, the ubiquity of massive continuously generated data streams poses an enormous challenge...

With increasing amounts of experimental data, openness, fairness, and reproducibility of scientific experimental work have become important factors for researchers, journals and funding bodies. However, these kinds of challenges are not easily and directly achievable. The goal of this paper is&#x...

In this paper, we are presenting a method and a tool that allows detecting duplicity in the heap dump of a Java application, based on the shallow and deep object comparison. The tool allows to identify the problematic instances in the memory and thus helps programmers...

As the number of digitized archival documents increases very rapidly, named entity recognition (NER) in historical documents has become very important for information extraction and data mining. For this task an annotated corpus is needed, which has up to now been missing for Czech...