In recent years, word embeddings have been shown to improve the performance in NLP tasks such as syntactic parsing or sentiment analysis. While useful, they are problematic in representing ambiguous words with multiple meanings, since they keep a single representation for each word in the vocabulary. Constructing separate embeddings for meanings of ambiguous words could be useful for solving the Word Sense Disambiguation (WSD) task. In this work, we present how a word embeddings average- based method can be used to produce semantic-rich meaning embeddings, and how they can be improved with distance optimization techniques. We also open-source a WSD dataset that was created for the purpose of evaluating methods presented in this research.
Educating young software engineers and IT experts is a great challenge nowadays. Still new technologies are used in a practical approach and many of them come from formal methods. To help future software experts in the understanding of formal methods grounded in semantics, learning software that illustrates and visualizes important techniques seems to be very fruitful. In this paper, we present software, which handles the arithmetic and Boolean expressions, their analysis, evaluation, drawing the syntax tree and the other techniques with the expressions. This software is devoted as a teaching tool for teachers when explaining appropriate theory and for students for self-studying and making their own experiments. Furthermore, this software is an integral part of our software package for several semantic methods.
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In this article the algorithm for automated detection of non-relevant or wrong information on websites is introduced. The algorithm extracts the semantic information from the webpage using third party software and compares the semantic information with the reliable resources. Reliable information is identified by the means of majority voting or extracted from reliable databases.
In spite of the fact that modern statistical and neural net based tools for parsing natural language texts supersede classical approaches there are still areas where generative grammars are used. These are areas where collection of universal parallel corpuses is still in the progress. National sign languages are among them. Ontologies and common sense databases play valuable role in parsing and translation of such languages. Grammatically augmented ontology (GAO) is an ontology extension that links phrases to their meaning. The link is established via special expressions that connect phrase meaning to grammatical and semantical attributes of words that constitute it. The article introduces a new approach to sentence parsing that is based on integration of ontology relations into productions of weighted affix context-free grammar (WACFG). For that reason a new parser for WACFG grammar was developed inspired by works of C.H.A. Koster. Basic properties of WACFG are discussed and the algorithm for selection and convertion of GAO expressions into the set of WACFG productions is provided. The proposed algorithm turned out to be feasible in the context of parsing and translating Ukrainian Spoken and Ukrainian Sign language. The developed approach for mixed semantical and syntactical sentence parsing was tested on the database of sentences from Ukrainian fairy tail by Ivan Franko “Fox Mykyta” where 92 % of sentences were correctly parsed.
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The parsing of a symbolic sequence into a set of short substrings called words invented by the author is used for a new definition of the distance between sequences. No sequence alignment is necessary. The most frequent among spectra of multiprotein sequences are selected and considered as a reference spectrum of the sequences. The distance between the reference spectrum and protein sequences is considered as the estimation of the evolutionary distance of the protein. As an application, amino acid sequences of the several mitochondria-encoded proteins of mammal species are ordered according to their evolutionary distance. Statistical distribution of the distances between exhibits some structures related to the evolutionary rate in the past.
This paper is focused on the process of computing First Sets. The First Sets are used to build structures which control a syntax analyser (also known as parser). Three methods of creating First Sets were compared in terms of execution time. The first method is known sequential algorithm and the author’s own methods are concurrent computing sets for each non-terminal symbol (called the CEN method) and concurrent computing sets for each production (called the CEP method). These methods have been tested on personal computer. Three programming languages (including the C language) were used in the research. The results and the analysis of calculations allow the author to hypothesise that the problem of computing First Sets is hard to concurrence.
W artykule przedstawiono koncepcję schematu sprawdzania kompletności danych po procesie ich transformacji opracowaną na potrzeby wymiany informacji pomiędzy różnymi systemami informatycznymi przetwarzającymi informacje w przedsiębiorstwie produkcyjnym. Scharakteryzowano pokrótce mechanizm konwersji informacji wykorzystywany podczas ich przepływu pomiędzy systemami informatycznymi przedsiębiorstwa. Opisano problematykę utraty części danych w trakcie ich przekształcania. Zaprezentowano opracowany algorytm a także wyniki działania programu go implementującego.
EN
The paper presents newest version of data completeness verification algorithm used in the process of its transformation elaborated for the information exchange between different systems in manufacturing company. Data conversion mechanism used in information flow between enterprise systems was characterized. Problems of data loss during the conversion process were described. Results of working of the program which implements the algorithm were presented.
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Some methods of automatic verification of cryptographic protocols require creating specially designed formal languages based on suitable algebra of terms (called crypto-terms or crypto-messages). Sometimes in verification process it is essential to check whether a given crypto-term is a sub term of another one or in general whether some crypto-term belongs to the specified crypto-Language (a set of some crypto-terms) or not. Another problem is creating the set of all ant chains of subterms of a given term wit h respect to the order introduced by a subterm relation. The main goal of this paper is to present a tool for verification whether crypto-term belongs to the specified crypto-language or not. Our main purpose is to check lexical analysis and syntax analysis. Finally, after checking that a crypto-sentence is correct, we convert it into the special format, purpose was to check lexical analysis and syntax analysis. For our investigation Flex and Bison - the well known grammar tools – have been used. We believe that our tool will be usefull in research on the topic of symbolic verification of cryptographic protocols.
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