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Varghese, Navitha
- Clustering Method for Predicting Actions of a Human Being at Different Locations
Authors
1 Department of Computer Science and Engineering, Karunya University, Coimbatore, Tamil Nadu, IN
Source
Data Mining and Knowledge Engineering, Vol 3, No 4 (2011), Pagination: 246-250Abstract
Human behavior can be characterized by a set of sequential action patterns. As such, there can be a causal relationship among actions. When these actions take place in uncertain conditions, it is difficult to predict the next action based on the observed actions. Thus, it would be a challenging task to establish some causal relationships among the sequential actions under observation .Some techniques are used for labeling actions which also deals with predicting actions. Further, we want to point out potential pitfalls as well as challenging issues of different techniques. We believe that the results of this evaluation will help for building up an autonomous system.Keywords
Prediction, HMM, CRF, AIBFC, Human Behavior.- Protection of Data from a Semi-Honest Party Using Fast Association Rule Hiding
Authors
1 Karunya University, IN
Source
Data Mining and Knowledge Engineering, Vol 3, No 1 (2011), Pagination: 67-70Abstract
Data mining technique is an emerging technique applied in strategic decision-making as well as in many more application areas. Nevertheless, it also has a few demerits apart from its utility. The data mining tools may bring out information that should not be disclosed to a semi honest party. Different approaches are being used to hide the sensitive information. This paper proposes a novel method to access the generating transactions from the transactional database. It helps in reducing the time and space complexities of any hiding algorithm. Theoretical and empirical analysis of the algorithm shows that hiding of data using this proposed technique performs association rule hiding quicker than other algorithms.