Efficient data manipulation in document classification

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Document Classification has an enormous relevance in an era where large amounts of textual information is available. Document Classification is based on statistical and machine learning techniques that model documents represented as points in a multidimensional space. The Computer Engineering Laboratory (CEL) has ongoing projects using neural networks and other techniques for document classification. We are developing a development environment for large classification tasks, and Prof. Lee¡¯s work will focus in managing large amounts of data for them. Using his experience in data compression, databases and web applications, he will produce a set of tools for handling Gigabytes of textual data in our classification environment.