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How Fuzzy Set Theory Can Help Make Database Systems More Cooperative

In this thesis, we are interested in how we can leverage fuzzy logic to improve the interactions between relational database systems and humans. Cooperative answering techniques aim to help users harness the potential of DBMSs.
These techniques are expected to be robust and always provide answers to users. Empty set (0,00 sec) is a typical example of answer that one may wish to never obtain. The informative nature of explanations is higher than that of actual answers in several cases, e.g. empty answer sets and plethoric answer sets, hence the interest of robust cooperative answering techniques capable of both explaining and improving an answer set.
Using terms from natural language to describe data --- with labels from fuzzy vocabularies --- contributes to the interpretability of explanations. Offering to define and refine vocabulary terms increases the personalization experience and improves the interpretability by using the user's own words.

We propose to investigate the use of explanations in a cooperative answering setting using three research axes: 1) in the presence of a plethoric set of answers; 2) in the context of recommendations; 3) in the context of a query/answering problem. These axes define cooperative techniques where the interest of explanations is to enable users to understand how results are computed in an effort of transparency. The informativeness of the explanations brings an added value to the direct results, and that in itself represents a cooperative answer.

Aurélien Moreau
Tuesday, 26. June 2018 - 9:00
ENSSAT Lannion, amphithéâtre 137C
Defense Type: 
Composition of jury: 

    Allel Hadjali, Professeur, ISAE-ENSMA, reviewer
    Marie-Jeanne Lesot, Maître de conférences HDR, Sorbonne Université, reviewer
    Dominique Laurent, Professeur, Université de Cergy-Pontoise, examiner
    Arnaud Martin, Professeur, Université de Rennes 1, examiner
    Olivier Pivert, Professeur, ENSSAT, advisor
    Grégory Smits, Maître de conférences HDR, Université de Rennes 1, advisor