Improving Ontology Recommendation and Reuse in WebCORE by Collaborative Assessments

In this work, we present an extension of CORE [8], a tool for Collaborative Ontology Reuse and Evaluation. The system receives an informal description of a specific semantic domain and determines which ontologies from a repository are the most appropriate to describe the given domain. For this task, the environment is divided into three modules. The first component receives the problem description as a set of terms, and allows the user to refine and enlarge it using WordNet. The second module applies multiple automatic criteria to evaluate the ontologies of the repository, and determines which ones fit best the problem description. A ranked list of ontologies is returned for each criterion, and the lists are combined by means of rank fusion techniques. Finally, the third component uses manual user evaluations in order to incorporate a human, collaborative assessment of the ontologies. The new version of the system incorporates several novelties, such as its implementation as a web application; the incorporation of a NLP module to manage the problem definitions; modifications on the automatic ontology retrieval strategies; and a collaborative framework to find potential relevant terms according to previous user queries. Finally, we present some early experiments on ontology retrieval and evaluation, showing the benefits of our system

Flood risk assessment in an urban area: Vila Nova de Gaia

This paper proposes a methodology for flood risk assessment in a non fluvial urban flood. Two hazard classifications were considered; one with water depth and flow velocity classes and other with the product of water depth and flow velocity. The vulnerability assessment resulted in five classes obtained by cluster and principal components analysis. Flood risk maps were achieved by hazard and vulnerability classes’ crossover. The methodology is applied to a case study in the city of Vila Nova de Gaia. DTM with one meter resolution; HEC-HMS and HEC-RAS was applied to an urban catch- ment with one hour temporal scale; the 2001 statistical census tracts provide the demographic and social information. This methodology can be considered a straightforward and successful way to assess flood risk maps. However, the differences attained by the two hazard methods point out the need of further developments in the assessment of flood risk in stepped urban areas

Personalized content retrieval in context using ontological knowledge

Personalized content retrieval aims at improving the retrieval process by taking into account the particular interests of individual users. However, not all user preferences are relevant in all situations. It is well known that human preferences are complex, multiple, heterogeneous, changing, even contradictory, and should be understood in context with the user goals and tasks at hand. In this paper, we propose a method to build a dynamic representation of the semantic context of ongoing retrieval tasks, which is used to activate different subsets of user interests at runtime, in a way that out-of-context preferences are discarded. Our approach is based on an ontology-driven representation of the domain of discourse, providing enriched descriptions of the semantics involved in retrieval actions and preferences, and enabling the definition of effective means to relate preferences and context

Optimized Monte Carlo Method for glasses

A new Monte Carlo algorithm is introduced for the simulation of supercooled liquids and glass formers, and tested in two model glasses. The algorithm is shown to thermalize well below the Mode Coupling temperature and to outperform other optimized Monte Carlo methods. Using the algorithm, we obtain finite size effects in the specific heat. This effect points to the existence of a large correlation length measurable in equal time correlation functions.Comment: Proceedings of "X International workshop on Disordered Systems" held in Molveno (Italy), March 200