Semantic Access to Data from the Web

There is a great amount of information available on the web. So, users typically use different keyword-based web search engines to find the information they need. However, many words are polysemous and therefore the output of the search engine will include links to web pages referring to different meanings of the keywords. Besides, results with different meanings are mixed up, which makes the task of finding the relevant information difficult for the user, specially if the meanings behind the input keywords are not among the most popular in the web. In this paper, we propose a semantics-based approach to group the results returned to the user in clusters defined by the different meanings of the input keywords. Differently from other proposals, our method considers the knowledge provided by a pool of ontologies available on the Web in order to dynamically define the different categories (or clusters). Thus, it is independent of the sources providing the results that must be grouped.