Traditional database systems have worked well for many years, becoming an essential part of considerable informational developments and being implemented extensively.
In addition, they are of great importance for the decision making of an organization, providing tools to analyze large amounts of data. Database systems support a large number of transactions, as well as high reliability and availability.
We are living in an era where organizations, in general, collect, maintain and use large amounts of information about their customers, suppliers and operations, while with the help of the use of mobile devices, the web every day is friendlier to all types of user.
Emerging paradigms such as the Internet of Things, sensor websites, environmental intelligence, intelligent environments and social networks all contribute to complicating this panorama in terms of the amount of data that is produced. These approaches also emphasize the tendency to make and maintain a stronger connection between computer applications and the real world.
The large volume of data provided by the use of technologies, if not filtered properly, overwhelms users, losing the opportunity to use the valuable knowledge that can be extracted from this data.
In addition to the techniques provided by various investigations (synthesis, understanding and analysis of large volumes of data), one way to help solve this problem is through the personalization of the systems since, in this way, the user will be provided with reduced information account for personal preferences and / or their situation.
In this sense, the development of applications sensitive to the context in Information Systems, contributes to improve the quality of access to information by the user through the personalization of applications. In this report we will present a proposal for a model for the development of sensitive applications to the context in Information Systems, specifically in the area of databases, characterized by being the least intrusive and most transparent to users, achieved through the use of recognized standards in that area, one of the purposes is to try to reproduce the virtual world what happens in the process of communication between people.
For this, we will also take into account the present imperfection in the data provided by the real world, especially those that are human in nature. The incorporation of fuzziness in the representation of the data is proposed, allowing, among other things, store values of linguistic variables and make consultation conditions more flexible.
Many researchers have successfully applied Zadeh’s fuzzy set theory  to model the imperfection of data in database management systems, thus approaching a more faithful representation of the natural language used by the human being, giving rise to what is more widely known as Fuzzy Databases.
That is why it was considered of interest to assume this theory for the proposal of the model object of study. traditional databases suffer from the problem of rigidity of They respond to queries in a precise and deterministic way (“exact match” query paradigm). In this case, a query provides answers (if any) that meet all the conditions established in that query. In addition, the Database Management System (DBMS) must guarantee that the same answer will always be obtained to a query.
This problem of the exact-coincidence query paradigm has two main drawbacks: 1) The emergency response, which can be addressed by relaxing some of the rigid restrictions in the query, that is, considering flexible constraints, reducing the user’s needs, replacing them with others that fit their preferences more adequately; 2) Too many responses, which can be faced through the strengthening of the consultation with additional conditions, expressing the user’s needs to limit the results, personalizing them