Amel Fraisse

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The n-gram model with a binary (or tf-idf) weighting scheme and an SVM classifier is a common approach which is used as a baseline in a lot of research on sentiment analysis and opinion mining. Other advanced methods are used on top of this model to improve the classification accuracy, such as generation of additional features or using supplementary(More)
This paper presents a logical formalization of a set 20 semantic categories related to opinion, emotion and sentiment. Our formalization is based on the BDI model (Belief, Desire and Intetion) and constitues a first step toward a unifying model for subjective information extraction. The separability of the subjective classes that we propose was assessed(More)
We propose a demonstration of our in context and collaborative software localisation model. It involves volunteer localisers and end users in the localisation process via an efficient and dynamic workflow: while using an application (in context), users knowing the source language of the application (often but not always English) can modify strings of the(More)
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