On modelling real-world knowledge to get answers to fuzzy and flexible searches without human intervention

The Internet has become a place where massive amounts of information and data are being generated every day. This information is most of the times stored in a non-structured way, but the times it is structured in databases it cannot be retrieved by using easy fuzzy queries. Being the information in the database the distance to the city center of some restaurants (and their names) by easy fuzzy queries we mean queries like "I want a restaurant close to the center". Since the computer does not have knowledge about the relation between being close to the center and the distance to the center (of a restaurant) it does not know how to answer this query by itself. We need human intervention to tell the computer from which database column it needs to retrieve data (the one with the restaurant's distance to the center), and how this non-fuzzy information is fuzzified (applying the close function to the retrieved value). Once this is done it can give an answer, just ordering the database elements by this new computed attribute. This example is very simple, but there are others not so simple, as "I want a restaurant close to the center, not very expensive and whose food type is mediterranean". Doing this for each existing attribute does not seem to be a very good idea. We present a web interface for posing fuzzy and flexible queries and a search engine capable of answering them without human intervention, just from the knowledge modelled by using the framework's syntax. We expect this work contributes to the development of more human-oriented fuzzy search engines.