01658nas a2200133   4500008004100000245006300041210006300104300001300167520116600180100002101346700002601367700002401393856010701417       2009                        eng d00aScalable Text Classification as a tool for Personalization0 aScalable Text Classification as a tool for Personalization  a 51 - 603 aWe consider scalability issues of the text classification problem where by
using (multi)-labeled training documents, we try to build classifiers that assign
documents into classes permitting classification in multiple classes. A new class of
classification problems; called ?scalable?, is introduced, with applications on web
mining. Scalable classification utilizes newly classified instances in order to improve the
accuracy of future classifications and capture changes in semantic representation of
different topics. In addition, definition of different similarity classes is allowed,
resulting in a ?per-user? classification procedure. Such an approach provides a new
methodology for building personalized applications. This is due to the fact that the user
becomes a part of the classification procedure. We explore solutions for the scalable text
classification problem and introduce an algorithm that exploits a new text analysis
technique that decomposes documents into the vector representation of their sentences
according to the user expertise. Finally, a web-based personalized news categorization
system that bases upon this approach is presented.1 aBouras, Christos1 aPoulopoulos, Vassilis1 aAntonellis, Ioannis  uhttp://telematics.upatras.gr/telematics/publications/scalable-text-classification-tool-personalization