Olga Nevzorova

OntoMath PRO Ontology: A Linked Data Hub for Mathematics

In this paper, we present an ontology of mathematical knowledge concepts that covers a wide range of the fields of mathematics and introduces a balanced representation between comprehensive and sensible models. We demonstrate the applications of this representation in information extraction, semantic search, and education. We argue that the ontology can be a core of future integration of math-aware data sets in the Web of Data and, therefore, provide mappings onto relevant datasets, such as DBpedia and ScienceWISE.

Mathematical knowledge representation: semantic models and formalisms

The paper provides a survey of semantic methods for solution of fundamental tasks in mathematical knowledge management. Ontological models and formalisms are discussed. We propose an ontology of mathematical knowledge, covering wide range of fields of mathematics. We demonstrate applications of this representation in mathematical formula search, and learning.

Bringing Math to LOD: A Semantic Publishing Platform Prototype for Scientific Collections in Mathematics

We present our work on developing a software platform for mining mathematical scholarly papers to obtain a Linked Data representation. Currently, the Linking Open Data (LOD) cloud lacks up-to-date and detailed information on professional level mathematics. To our mind, the main reason for that is the absence of appropriate tools that could analyze the underlying semantics in mathematical papers and effectively build their consolidated representation. We have developed a holistic approach to analysis of mathematical documents, including ontology based extraction, conversion of the article body as well as its metadata into RDF, integration with some existing LOD data sets, and semantic search. We argue that the platform may be helpful for enriching user experience on modern online scientific collections.

Digital Ecosystem OntoMath: Mathematical Knowledge Analytics and Management

A mathematical knowledge management technology is discussed, its basic ideas, approaches and results are based on targeted ontologies in the field of mathematics. The solution forms the basis of the specialized digital ecosystem OntoMath which consists of a set of ontologies, text analytics tools and applications for managing mathematical knowledge. The studies are in line with the project aimed to create a World Digital Mathematical Library whose objective is to design a distributed system of interconnected repositories of digitized versions of mathematical documents.

Towards Building Wordnet for the Tatar Language: A Semantic Model of the Verb System

Wordnet is a lexical database where nouns, verbs, adjectives, and adverbs are organized in a conceptual hierarchy linking semantically and lexically related concepts to each other. This paper reports on the prototype of the Tatar Wordnet which currently contains about 5,500 Tatar verbs. Within our project we are creating a model of the semantic system of Tatar verbs as a hierarchical structure considering specifics of the Tatar language. For this purpose we use the entries of available Tatar dictionaries (explanatory dictionaries and those of synonyms). As the first step the extraction of available verbal synonyms from the dictionary of synonyms of the Tatar language was carried out. Then the most frequent 5156 Tatar verbs were selected and classified into several groups (synsets) according to their dominant semantic components with the purpose of adding new synsets and enriching those already existing (currently about 1,500 core synsets were distinguished). Then semantic relations between synsets were mapped (the verbs were linked according to their troponymy, entailment, and causality). The paper presents the results obtained, and discusses some problems encountered along the way.

Russian-Tatar Socio-Political Thesaurus: Methodology, Challenges, the Status of the Project.

This paper discusses the general methodology and important practical aspects of implementing a new bilingual lexical resource – the Russian-Tatar Socio-Political Thesaurus that is being developed on the basis of the Russian RuThes thesaurus format as a hierarchy of concepts viewed as units of thought. Each concept is linked with a set of language expressions (words and collocations) referring to it in texts (text entries). Currently the Russian-Tatar Socio-Political Thesaurus includes 6,000 concepts, while new concepts and text entries are being constantly added to it. The paper outlines main challenges of translating concept names and their text entries into Tatar, and describes ways of reflecting the specificity of the Tatar lexical-semantic system.

Toward Domain-Specific Russian-Tatar Thesaurus Construction

The paper discusses the main principles and practical aspects of implementing a new bilingual lexical resource - the Russian-Tatar thesaurus on socio-political and IT issues. This thesaurus is developed on the basis of the Russian RuThes thesaurus format which is built as a hierarchy of concepts viewed as units of thought, with each concept linked to a set of language expressions that refer to it in texts (text entries). The paper discusses general methodology of translating concept names and their text entries, as well as ways of reflecting the specificity of the Tatar lexical-semantic system.

RuThes Cloud: Towards a Multilevel Linguistic Linked Open Data Resource for Russian

In this paper we present a new multi-level Linguistic Linked Open Data resource for Russian. It covers four linguistic levels: semantic, lexical, morphological and syntactic. The resource has been constructed on base of the well-known RuThes thesaurus and the original hitherto unpublished Extended Zaliznyak grammatical dictionary. The resource is represented in terms of SKOS, Lemon, and LexInfo ontologies and a new custom ontology. Building the resource, we automatically completed the following tasks: merging source resources upon common lexical entries, decomposing complex lexical entries, and publishing constructed resource as LLOD-compatible dataset. We demonstrate the use case in which the developed resource is exploited in IR task. We hope that our work can serve as a crystallization point of the LLOD cloud in Russian.

Semantic formula search in digital mathematical libraries

We are presenting semantic methods of search for mathematical objects in scientific publications. In particular, methods of search for mathematical formulas, as well as methods based on the logical structure of mathematical documents, are being discussed here. Based on the digital mathematical library Lobachevskii DML, created at Kazan Federal University in 2017, declared as Lobachevsky Year, we developed and tested new methods of search in digital collections of mathematical documents.

A syntactic method of extracting terms from special texts for replenishing domain ontologies

Natural Language Processing (NLP) is one of the principal areas of artificial intelligence. It can be argued that the use of ontologies increases the efficiency of natural language processing. However, most ontologies are built manually and require a lot of work. Thus, the problem of automated ontology replenishment is very relevant. One approach is to develop methods for replenishing ontologies using NLP for specific texts of a certain area. We applied the developed method of replenishing the OntoMathPro mathematical ontology, by extracting new terminology from mathematical documents. We developed a method for processing complex syntactic structures (structures with coordination reduction). The method includes certain rule schemata, conditions under which they are to be applied, and conditions determining the sequence of subtrees for which they are to be performed. In our studies, we investigated typical coordination models for mathematical works and performed experiments with a big mathematical collection.