Using Part-of-Speech Patterns and Domain Ontology to Mine Imprecise Concepts from Text Documents

In the last few years, several works in the literature have addressed the problem of information extraction from text documents. The importance of this problem derives from the fact that, once extracted, the information can be handled in a way similar to instances of a traditional database. But, most of the information extraction systems assume that the texts are having only precise concepts and these restrict the information provider to use only precise concepts to represent their information. In this paper we have presented a system that uses part-of-speech patterns and domain ontology to extract imprecise concepts present in the text documents and hence it allows information provider to describe concepts by using linguistic variables – very, more, light, strong, slightly, quite etc. that are very common with natural languages. We have considered wine documents as case study however it can be applied to any domain for which there is an existing ontology. In this paper, we have shown how a structured knowledgebase can be designed to hold imprecise concept descriptions extracted from text documents. The structured knowledgebase can then be searched efficiently for required information.