On the intelligent content retrieval by means of text relevance modelling

This paper presents some results with application in area of web-based knowledge retrieval. The key issue on the relevant topics retrieving in practice is that the results returned by the actual search engines do not provide fully satisfaction to the user in terms of his or her informational needs. Considering the information utility is correlated to the semantic meaning - that is: if the information has the expected meaning then it can be considered to be useful. A measure of information utility in the contents is given by the relevancy of the search terms. In our study we achieve a preliminary experimental investigation on the set of informational sources, comparing the ranking of the documents by three distinct methods. One is based on a fuzzy logic relevance filter that was proposed as an original method by the author in his previous work. Its outcomes are compared with the answers returned by a popular web search engine and also with the solutions provided by the user. This research aims to improve the technology of intelligent information retrieval to access the relevant e-content.