The market for medicines and parapharmacy is composed of many intermediary actors. Currently, information about the best trading conditions on the market is very difficult to access, hence pharmacies do not have a way of comparing their direct purchases. This project aims to create a decision support system for pharmacies in order to reduce their procurement costs and thus lower product prices that could in the end benefit for the patient. One important objective is to integrate and analyze the natural multilingual text from different formats and sources. Relying on semantic technologies, we transposed the complexity of current processes into a central system capable of managing the heterogeneity and large volume of information sources to ensure the velocity of the information system. The use of ontologies made it possible to determine unambiguously the nature of the links between the different data, and to build our own knowledge bases for sharing and reusing them later. Meanwhile, our semantic search engine allowed users to provide the synonyms based on the contextual meaning of words, it improved the search accuracy, and generated more relevant results.
