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Latent Semantic Indexing is a widely used text mining technology nowadays due its effectiveness in dealing with the problems of synonymy and polysemy within a proper matrix scale. However LSI is enormously computationally intensive especially for processing large scale data. And effective solution is to increase the computational power available to LSI using multiple computing nodes. In this paper...
The popularity of SVMs has grown tremendously in the last few years for many different classification problems due to its generalization properties, however training SVMs require high computational power. Platt's SMO is one the fastest algorithm for training support vector machines, which takes the decomposition technique to the extreme by selecting a set of only two points as the working set then...
Recently MapReduce programming model is becoming popular for large scale data intensive distributed applications due to its efficiency, simplicity and ease of use. The Hadoop implementation of MapReduce is one of the most popular tools for many programmers due its ability to hide details of parallel programming from the users. However work on simulating the Hadoop environment is still in its infancy...
The past decade has seen a rapid development in content based image retrieval (CBIR). CBIR is the retrieval of images based on their low level features such as color, texture, shape etc. To improve the retrieval accuracy, the research focus has been shifted from designing sophisticated low-level feature extraction algorithms to reducing the `semantic gap' between the visual features and the richness...
Healthcare data and medical information need to be seamlessly accessible and available at all times to the various healthcare stakeholders. Inability to share, integrate and access critical healthcare information is a challenge for the healthcare IT. Moreover, semantic interoperability of health-related heterogeneous data sources is a challenging issue and healthGrids are expected to address this...
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