Parametric and semantic analytical search indexes in hieroglyphic languages

Nowadays tremendous amounts of heterogeneous information known as Big Data have completely changed the modern scientific landscape. On the one hand, Big Data provides experts with massive opportunities for conducting research in almost every filed of human endeavor, developing novel technologies and disseminating scientific knowledge. On the other hand, a strong need for creating new techniques to handle Big Data has emerged. This paper is devoted to analytical search indexes, which allow researchers to obtain the information of interest from Big Data. Two types of analytical search indexes, namely parametric and semantic, are considered in the paper. Parametric search index will allow researchers to find information about a technology or material with specific physical parameters which values lie in the given interval, as opposed to the substring search, that enables researchers to find only a particular parameter value. The idea behind using semantic search index in this paper is based on the notion of the technology life cycle, which will allow identifying the current state of a particular technology. Existing models of life cycle have been analyzed and a new model has been suggested. The ontology of physical parameters and the life cycle ontology have been developed. The next step has been the development of the algorithm, which uses the corresponding ontologies to split, filter and mark texts and saves the results to the database for further use as search indexes. The Chinese language has been chosen as a hieroglyphic language for conducting this research.