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In this paper, we announce the development of Neural Monkey – an open-source neural machine translation (NMT) and general sequence-to-sequence learning system built over the TensorFlow machine learning library. The system provides a high-level API tailored for fast prototyping of complex architectures with multiple sequence encoders and decoders. Models'(More)
In the recent years a new type of NoSQL databases, called graph databases (GDBs), has gained significant popularity due to the increasing need of processing and storing data in the form of a graph. The objective of this paper is a research on possibilities and limitations of GDBs and conducting an experimental comparison of selected GDB implementations. For(More)
As the XML has become a standard for data representation , it is inevitable to propose and implement techniques for efficient managing of XML data. A natural alternative is to exploit features of (object-)relational database systems, i.e. to rely on their long theoretical and practical history. The main concern of such techniques is the choice of an(More)
Since XML becomes a crucial format for representing information, it is necessary to establish techniques for managing XML documents. A possible solution can be found in storing XML data in (object-)relational databases. For this purpose most of the existing techniques often exploit an XML schema of the stored XML data, usually expressed in DTD. But the more(More)
Change detection of XML data has emerged as an important research issue in the last decade, however the majority of change detection algorithms focuses on XML documents rather than schemas. This is because documents that contain data are deemed more significant than the schema itself. This paper looks at the problem from a different perspective by(More)