Random indexing is a method for constructing vector spaces at a reduced dimensionality. Previously, the method has been proposed using Kanerva's sparse distributed memory model. Although intuitively plausible, this ...

Vector space models (VSMs) are mathematically well-defined frameworks that have been widely used in the distributional approaches to semantics. In VSMs, high-dimensional vectors represent linguistic entities. In an ...

Microcontroller Units (MCUs) in edge devices are resource constrained due to their limited memory footprint, fewer computation cores, and low clock speeds. These limitations constrain one from deploying and executing machine ...

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Renewable energy sources are highly unreliable; hence prosumers connected to renewable energy sources find unreliable energy surplus and demands which should be managed frequently within neighbourhoods. Peer-to-peer(P2P) ...

Multiple datasets that add high value to biomedical research have been exposed on the web as a part of the Life Sciences Linked Open Data (LSLOD) Cloud. The ability to easily navigate through these datasets is crucial for ...

In today’s era of globalization, sustainable mobility is considered as a key factor in the economic growth of any country. With the emergence of open data initiatives, there is tremendous potential to improve mobility. ...

To profit in today¿s market, small manufacturers must be efficient and agile to minimise cost and to meet variable market demand. This paper discusses an envisaged Semantic, Ambient, Generic and Extensible framework ...

One of the key issues for the uptake of the Semantic Web idea is the availability of reasoning techniques that are usable on a large scale and that offer rich modeling capabilities by providing comprehensive coverage of ...

Statistical data is present everywhere from governmental bodies to economics, from life-science to industry. With the rise of the Web of Data, the need for sharing, accessing, and using this data has entered a new stage. ...