A Document Profile for Improving Information Retrieval Systems

Abstract

In recent year the great popularity that enjoys mobile technologies has led most users to become consumers and producers of information on the network. Many studies speak about this phenomenon as an activity that is capable of doubling or tripling existing content on an annual basis. The huge amount of information makes the current user oriented systems, like retrieval systems, recommender systems and others, become less efficient, especially when users require specific information and answers according to their needs and preferences. These facts make necessary to equip these systems with proper Natural Language technologies able to provide the information that users demand adapted to each context and content type. In this article, it is presented a study of some Natural Language Processing technologies that can be useful to facilitate the proper identification of documents according to the user needs. For this purpose, it is designed a document pro le that will be able to represent semantic meta-data extracted from documents. The research is basically focused on the study of different language technologies in order to support the creation this novel document profile proposal from semantic perspectives.