Martine de Cock

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As opposed to quantitative association rule mining, fuzzy association rule mining is said to prevent the overestimation of boundary cases, as can be shown by small examples. Rule mining, however, becomes interesting in large databases, where the problem of boundary cases is less apparent and can be further suppressed by using sensible partitioning methods.(More)
Various intelligent systems rely heavily on formalisms for spatial representation and reasoning. However, it is widely recognized that real-world regions are seldom characterized by a precisely defined boundary. This paper proposes a generalization of the region connection calculus (RCC) which allows to define spatial relations between vague regions. To(More)
Satisfiability in propositional logic is well researched and many approaches to checking and solving exist. In infinite-valued or fuzzy logics, however, there have only recently been attempts at developing methods for solving satisfiability. In this paper, we propose a new incomplete solver, based on a class of continuous optimization algorithms called(More)
The accurate prediction of forest fire size is important in order to issue adequate and timely warnings and to allocate fire-fighting assets efficiently and effectively. A forest fire data set collected in Portugal has recently become available as a benchmark for experimental validation of data mining techniques to tackle this problem. In this paper, we(More)
We pursue two strategies for offline data collection for a temporal question answering system that uses both quantitative methods and fuzzy methods to reason about time and events. The first strategy extracts event descriptions from the structured year entries in the online encyclopedia Wikipedia, yielding clean quantitative temporal information about a(More)
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