DSC/e Lecture Marie-Jeanne Lesot
25 april | Kamer van Koophandel, Kennispoort (Grote Zaal), J.F. Kennedylaan 2, EINDHOVEN | DSC/e | Website
Extracting knowledge in linguistic form
Machine learning can be seen as aiming to allow users to understand the huge quantities of data they are faced with. One way to facilitate interpretation of the results consists in presenting them in natural language, offering linguistic expressions which may be easier to understand. The choice of such result formulation then has an impact on the machine learning techniques to be applied to the data. This talk will present three tasks in this framework, considering different types of data.
The first task aims at extracting gradual item sets from numerical data, as well as contextual variants thereof, linguistically expressing information about the feature co-variations, as illustrated by the example "the higher the speed, the greater the danger". A second task aims at summarizing temporal series, in particular their periodicity, using the specific quantifier "regularly". In both cases, the question is to precisely define the associated semantics and to define efficient extraction algorithms. A third task investigates the measure of the relevance of the linguistic terms used to express the summaries, both with respect to the data structure, in case of linguistic variables, and with respect to the cognitive interpretation, in case of approximate numerical expressions.
Full abstract & biography Marie-Jeanne Lesot
12:00 Doors open
12.30-13.30 Lecture by Marie-Jeanne Lesot