Problem statement:The way of referring to a place in the geographical space can be formal, based on the spatial coordinates, or informal, which we use in natural language by using toponyms (place names). A toponym can represent several geographical places. This ambiguity made problematic its conversion towards a unique formal representation. Toponym disambiguation in text is the task of assigning a unique location to an ambiguous place name in a given textual context. Approach: Several toponym disambiguation heuristics assumed a geographical proximity between the toponyms of the same context. This proximity can be in terms of spatial distance or in terms of arborsecent relationships, i.e., proximity in the hierarchical tree of the world places. This study presented a new toponym disambiguation heuristic in text based on the quantification of the arborescent proximity between toponyms. This quantification was done by a new measure of geographical correlation that we call the Geographical Density. Results: Our method was compared to the state of the art methods using GeoSemCor corpus and it has outperformed them in term of recall (87.4%) and coverage (99.0%). The results showed that the toponyms of the same context are much closer in terms of arborescent relationships than in terms of spatial relationships. Conclusion: We believe that the quantification of arborescent relationships between toponyms of the same textual context is a good way to improve the recall of TD task. However, all the arborescent relationships' types must be considered and not only the meronymy, which is the relation the most exploited in the existing TD methods.
International audienceThis work falls in the areas of information retrieval and semantic web, and aims to improve the evaluation of web search tools. Indeed, the huge number of information on the web as well as the growth of new inexperienced users creates new challenges for information retrieval; certainly the current search engines (such as Google, Bing and Yahoo) offer an efficient way to browse the web content. However, this type of tool does not take into account the semantic driven by the query terms and document words. This paper proposes a new semantic based approach for the evaluation of information retrieval systems; the goal is to increase the selectivity of search tools and to improve how these tools are evaluated. The test of the proposed approach for the evaluation of search engines has proved its applicability to real search tools. The results showed that semantic evaluation is a promising way to improve the performance and behavior of search engines as well as the relevance of the results that they return
This paper proposes a new design approach for U-Healthcare systems. Our approach consists in combining the generic observer/controller architecture of organic computing, ontologies and rule-based paradigms. This combination brings three significant benefits. First, it allows keeping the system highly supervised and controlled by the observer/controller. Secondly, it enables the system to reason upon useful contextual information gathered from different and heterogeneous entities, and deduce new situations that require adaptation of the system's behaviour. Finally, it enables the system to adapt its behaviour dynamically to the context change by reasoning about this context and selecting the appropriate service to a specific user.
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