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. The paper discusses the problem of modelling linguistic uncertainty, which is the uncertainty produced by statements in natural language. For example, the vague statement `Mary is young' produces uncertainty about Mary's age. We concentrate on simple affirmative statements of the type `subject is predicate', where the predicate satisfies a special condition called monotonicity. For this case, we model linguistic uncertainty in terms of upper probabilities, which are given a behavioural interpretation as betting rates. Possibility measures and probability measures are special types of upper probability measure. We evaluate Zadeh's suggestion that possibility measures should be used to model linguistic uncertainty and the Bayesian claim that probability measures should be used. Our main conclusion is that, when the predicate is monotonic, possibility measures are appropriate models for linguistic uncertainty. We also discuss several assessment strategies for constructing a numerical mo...

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Abstract. This chapter focuses on real-world applications of fuzzy techniques for information retrieval and data mining. It gives a presentation of the theoretical background common to all applications, lying on two main elements: the concept of similarity and the fuzzy machine learning framework. It then describes a panel of real-world applications covering several domains namely medical, educational, chemical and multimedia. 1

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Institute of Technologies guide to producing literature reviews. This short handout is not the definitive guide on how to write a literature review. It is however a collection of some handy hints to point you in the right direction. You wouldn’t want all of the work done for you now would you? What is a Literature Review? The literature review is a critical look at the existing research that is significant to the work that you are carrying out. Be mindful of the fact that a literature review is not a summary. Although summarisation of others work is important, you have to evaluate this work, show relationships between different work and finally, show how previous work relates to your own work. You cannot simply describe other peoples work. Consider the following diagram: 1

perceive, understand, and managemultidimensional information with visualizations