Automated extraction of concept matcher thesaurus from semi structured catalogue like sources of data on the web
Ontology design and the process of populating a data set with knowledge following the chosen or developed ontology to fit the principles of Semantic Web and Linked Open Data is a time consuming and iterative process, requiring either expert knowledge or a set of tools for data scraping from web. A valid and consistent ontology and knowledge withing the data set require unification of concepts which means overcoming ambiguity and synonymy of terms which become individuals of ontology. In this paper we spot on techniques used for organising a Russian food product data set under a light weight FOOD Ontology and concept matching in particular. Main approaches to data set concept unification, synonymic term matching and ways to collect dictionaries for matcher are mentioned. The tool for catalogue like semi structured resources parsing and thesaurus extraction is developed and introduced for the task of on the fly concept matching.
2016 18th Conference of Open Innovations Association and Seminar on Information Security and Protection of Information Technology (FRUCT ISPIT)