Semantic technologies are rapidly changing the historical research. Over the last decades, an immense amount of new quantifiable data have been accumulated, and made available in interchangeable formats, in social sciences and humanities, opening up new possibilities for solving old questions and posing new ones. This paper introduces a framework that eases the access of scholars to historical ...

Abstract. The growing di↵usion of IT-based services generates a lot of data useful for supporting the activities of firms, organisations, and state agencies. In such a context, data quality tasks are frequently addressed using cleansing routines, often framed in the wider context of ETL processes (Extraction, Transformation, and Loading). The design of these cleansing routines often relies on t...

In studies involving medical devices, standardization of data formats of medical devices is still an open problem. Although some standards exist, manufacturers often implement their own proprietary format or use competing standards. Furthermore, especially during the development of a medical device the data format may change. Therefore, flexible means to integrate different kinds of data source...

We introduce a simulation optimization approach that is effective in guiding the search for optimal values of input parameters to a simulation model. Our proposed approach, which includes enhanced data mining methodology and state-of-the-art optimization technology, is applicable to settings in which a large amount of data must be analyzed in order to discover relevant relationships. Our approa...

We describe a knowledge based system for microbiological laboratory data validation and bacteria infections monitoring. The knowledge base has been obtained from international standard guidelines for microbiological laboratory practice, from experts’ suggestions and from data mining. In this work, we evaluate the system in terms of accuracy on a test dataset.

Abstract— High-performance computing and vast storage are two key factors required for executing data-intensive applications. In comparison with traditional distributed systems like data grid, cloud computing provides these factors in a more affordable, scalable and elastic platform. Furthermore, accessing data files is critical for performing such applications. Sometimes accessing data becomes...

Recommender systems have been widely used in e-commerce applications. They are a subclass of information filtering system, used to either predict whether a user will prefer an item (prediction problem) or identify a set of k items that will be user-interest (Top-k recommendation problem). Demanding sufficient ratings to make robust predictions and suggesting qualified recommendations are two si...

This study deals with the 3D recovering of magnetic susceptibility model by incorporating the sparsity-based constraints in the inversion algorithm. For this purpose, the area under prospect was divided into a large number of rectangular prisms in a mesh with unknown susceptibilities. Tikhonov cost functions with two sparsity functions were used to recover the smooth parts as well as the sharp ...