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2002

Oliveira, Stanley, Zaiane, Osmar

Technical report TR02-13. Discovering hidden patterns from large amounts of data plays an important role in marketing, business, medical analysis, and other applications where these patterns are paramount for strategic decision making. However, recent research has shown that some discovered...

2003

Oliveira, Stanley, Zaiane, Osmar

Technical report TR03-15. In this paper, we address the problem of protecting some sensitive knowledge in transactional databases. The challenge is on protecting actionable knowledge for strategic decisions, but at the same time not losing the great benefit of association rule mining. To...

2000

Zaiane, Osmar, Ammoura, Ayman

Technical report TR00-17. A system, DIVE-ON, was developed for visualizing and interacting with data from distributed data warehouses in an immersed virtual reality environment called a CAVE. The system provides navigation operations, OLAP manipulations, and data selection and filtering...

2001

Antonie, Maria-Luiza, Zaiane, Osmar

Technical report TR01-04. Discriminating between text articles and automatically classifying documents is an essential task for many applications. With the prevalence of digital documents and the wide use of e-mail and web documents, text categorization is regaining interest and is becoming a...

2002

Zaiane, Osmar, Wang, Weinan

Technical report TR02-07. Clustering means grouping similar objects into groups such that objects within a same group bear similarity to each other while objects in different groups are dissimilar to each other. As an important component of data mining, much research on clustering has been...

2002

Lee, Chi-Hoon, Foss, Andrew, Zaiane, Osmar, Wang, Weinan

Technical report TR02-03. Clustering is the problem of grouping data based on similarity and consists of maximizing the intra-group similarity while minimizing the iter-group similarity. While this problem has attracted the attention of many researchers for many years, we are witnessing a...

2001

Lu, Paul, El-Hajj, Mohammad, Zaiane, Osmar

Technical report TR01-12. Searching for frequent patterns in transactional databases is considered one of the most important data mining problems. Most current association mining algorithms, whether sequential or parallel, adopt an apriori-like algorithm that requires full multiple I/O scans of...

2003

Oliveira, Stanley, Zaiane, Osmar

Technical report TR03-12. Despite its benefit in a wide range of applications, data mining techniques also have raised a number of ethical issues. Some such issues include those of privacy, data security, intellectual property rights, and many others. In this paper, we address the privacy problem...

2003

El-Hajj, Mohammad, Zaiane, Osmar

Technical report TR03-08. Existing association rule mining algorithms suffer from many problems when mining massive transactional datasets. One major problem is the high memory dependency: either the gigantic data structure built is assumed to fit in main memory, or the recursive mining process...

2004

Antonie, Maria-Luiza, Zaiane, Osmar

Technical report TR04-07. Typical association rules consider only items enumerated in transactions. Such rules are referred to as positive association rules. Negative association rules also consider the same items, but in addition consider negated items (i.e. absent from transactions). Negative...