Lunchtime Seminar - Smart Answering of Database Queries in the Presence of Uncertainty - A Semiotic-Inspired Approach
The increasing amount of data being generated on a daily basis has empowered the development of novel products and services. However, this data deluge has clear impacts on our everyday lives, turning usual activities, such as selecting destinations for vacation, choosing a movie on a streaming platform, or purchasing a suitable car, into puzzling situations in which there is no standard method to find an appropriate decision. To solve problems like these, personalized applications (from Web search engines to Recommender Systems) allow people to focus on useful options considering individual or group interests. Nonetheless, even when supported by systems like these, one can often notice that interesting options were not covered in a system's response. This is frequently caused by the fact that, when dealing with such decision problems, one frequently only has a vague idea about which characteristics are expected to be found in the final solution. In this talk, the concept of Semiotic Machine will be introduced, a query refinement process for tackling uncertainty and vagueness in database queries. Moreover, a small case will be presented for materializing the ideas and for guiding further research avenues.
Denis Martins holds a Master’s degree in Computer Engineering from the University of Pernambuco, Brazil. He is a doctoral candidate at Prof. Vossen’s Chair for Databases and Information Systems at the University of Münster. His research interests focus on Computational Intelligence and Computational Semiotics, with emphasis on intelligent decision-making support in Big Data scenarios.