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The accurate prediction of Web navigation patterns has immense commercial value as the Web evolves into a primary medium for marketing and sales for many businesses. Often these predictions are based on complex temporal models of users' behavior learned from historical data. Such an approach, however, is not readily understandable by business people and(More)
Text document clustering is a popular task for understanding and summarizing large document collections. Besides the need for efficiency, document clustering methods should produce clusters that are readily understandable as collections of documents relating to particular contexts or topics. Existing clustering methods often ignore term-document semantics(More)
Ideally, document clustering methods should produce clusters that are semantically relevant and readily understandable as collections of documents belonging to particular contexts or topics. However, existing popular document clustering methods often ignore term-document corpus-based semantics while relying upon generic measures of similarity. In this(More)
We describe and evaluate a discriminative clustering approach for content-based tag recommendation in social bookmarking systems. Our approach uses a novel and efficient discriminative clustering method that groups posts based on the textual contents of the posts. The method also generates a ranked list of discriminating terms for each cluster. We apply the(More)
In this paper, we propose and evaluate a self-optimization strategy for a clustering-based tag recommendation system. For tag recommendation, we use an efficient discriminative clustering approach. To develop our self-optimization strategy for this tag recommendation approach, we empirically investigate when and how to update the tag recommender with(More)
The Online Shopping Experience has opened the new ways of business and shopping. Now the traditional terms of shopping have been changed and new terms to shop online emerge into customers' online shopping behaviors and preferences. Extracting interesting shopping patterns from ever increasing data is not a trivial task. We need intelligent association rule(More)
Face recognition from an image is a popular problem in biometrics research. In the last decade, a lot of research has been done in this area. The advantage of face based identification over other biometrics is its wide acceptability as it does not require any keys, tokens, smart cards, PINs, plastic cards or passwords, etc. In this work, face recognition(More)
Autonomic and autonomous systems exist within a world view of their own. This world view is created from the training data and assumptions that were available at their inception. In most of these systems this world view becomes obsolete over time due to changes in the environment. This brings a level of inaccuracy in the autonomic behavior of the system.(More)
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