A Survey on IT-Techniques for a Dynamic Emergency Management in Large Infrastructures

This deliverable is a survey on the IT techniques that are relevant to the three use cases of the project EMILI. It describes the state-of-the-art in four complementary IT areas: Data cleansing, supervisory control and data acquisition, wireless sensor networks and complex event processing. Even though the deliverable’s authors have tried to avoid a too technical language and have tried to explain every concept referred to, the deliverable might seem rather technical to readers so far little familiar with the techniques it describes

Interactional Structure Applied to the Identification and Generation of Visual Interactive Behavior: Robots that (Usually) Follow the Rules

Peer reviewe

Negation 'presupposition' and metarepresentation: a response to Noel Burton-Roberts

Metalinguistic negation (MN) is interesting for at least the following two reasons: (a) it is one instance of the much broader, very widespread and various phenomenon of metarepresentational use in linguistic communication, whose semantic and pragmatic properties are currently being extensively explored by both linguists and philosophers of language; (b) it plays a central role in recent accounts of presupposition-denial cases, such as ‘The king of France is not bald; there is no king of France’. It is this latter employment that discussion of metalinguistic negation has focused on since Horn (1985)'s key article on the subject. While Burton-Roberts (1989a, 1989b) saw the MN account of presupposition-denials as providing strong support for his semantic theory of presupposition, I have offered a multi-layered pragmatic account of these cases, which also involves MN, but maintains the view that the phenomenon of presupposition is pragmatic (Carston 1994, 1996, 1998a)

Towards the Automatic Classification of Documents in User-generated Classifications

There is a huge amount of information scattered on the World Wide Web. As the information flow occurs at a high speed in the WWW, there is a need to organize it in the right manner so that a user can access it very easily. Previously the organization of information was generally done manually, by matching the document contents to some pre-defined categories. There are two approaches for this text-based categorization: manual and automatic. In the manual approach, a human expert performs the classification task, and in the second case supervised classifiers are used to automatically classify resources. In a supervised classification, manual interaction is required to create some training data before the automatic classification task takes place. In our new approach, we intend to propose automatic classification of documents through semantic keywords and building the formulas generation by these keywords. Thus we can reduce this human participation by combining the knowledge of a given classification and the knowledge extracted from the data. The main focus of this PhD thesis, supervised by Prof. Fausto Giunchiglia, is the automatic classification of documents into user-generated classifications. The key benefits foreseen from this automatic document classification is not only related to search engines, but also to many other fields like, document organization, text filtering, semantic index managing