Edinburgh Napier University

A rule based taxonomy of dirty data.

Journal Article

Li, L., Peng, T., & Kennedy, J. (2011)

A rule based taxonomy of dirty data. GSTF journal on computing, 1(2), 140-148

There is a growing awareness that high quality of data is a key to today’s business success and that dirty data existing within data sources is one of the causes of poor data ...

An evaluation of name matching techniques.

Conference Proceeding

Peng, T., Li, L., & Kennedy, J. (2011)

An evaluation of name matching techniques. In Proceedings of 2nd Annual International Conference on Business Intelligence and Data Warehousing

Abstract—There is a growing awareness that the high quality of string matching is a key to a variety of applications, such as data integration, text and web mining, informatio...

Improving data quality in data warehousing applications

Conference Proceeding

Li, L., Peng, T., & Kennedy, J. (2010)

Improving data quality in data warehousing applications. In J. Filipe, & J. Cordeiro (Eds.), Proceedings of the 12th International Conference on Enterprise Information Systems, 379-382. https://doi.org/10.5220/0002903903790382

There is a growing awareness that high quality of data is a key to today’s business success and dirty data that exits within data sources is one of the reasons that cause poor...

The VoIP intrusion detection through a LVQ-based neural network.

Presentation / Conference

Zheng, L., & Peng, T. (2009, November)

The VoIP intrusion detection through a LVQ-based neural network. Paper presented at The 4th International Conference for Internet Technology and Secured Transactions, London, UK

Being a fast-growing Internet application, Voice over Internet Protocol shares the network resources with the regular Internet traffic. However it is susceptible to the existi...

A framework for data cleaning in data warehouses

Journal Article

Peng, T. (2008)

A framework for data cleaning in data warehouses. Enterprise Information Systems, 473-478

It is a persistent challenge to achieve a high quality of data in data warehouses. Data cleaning is a crucial task for such a challenge. To deal with this challenge, a set of ...

Combining dimensional analysis and heuristics for causal ordering.

Book

Shen, Q., & Peng, T. (2006)

Combining dimensional analysis and heuristics for causal ordering. In A. Bundy, & S. Wilson (Eds.), Rob Milne: A Tribute to a Pioneering AI Scientist, Entrepreneur and Mountaineer, 39-53. IOS Press

This paper is a refined version of the work that the authors presented at the 13th International Workshop on Qualitative Reasoning, jointly with the late Dr Rob Milne. It is d...

Towards a framework for dealing with data quality in data warehouses.

Book

Peng, T. (2005)

Towards a framework for dealing with data quality in data warehouses. In P. Petratos (Ed.), Current Computing Developments in E-Commerce, Security, HCI, DB, Collaborative and Cooperative Systems, 241-256. ATINER

The popularity of data warehouses (DWs) in recent years confirms the importance of data quality in today’s business success. It is estimated that as high as 75% of the effort ...

Best practice for implementing a data warehouse: a review for strategic alignment.

Conference Proceeding

Weir, R., Peng, T., & Kerridge, J. (2003)

Best practice for implementing a data warehouse: a review for strategic alignment. In Design and Management of Data Warehouses 2003: Proceedings of the 5th Intl. Workshop DMDW'2003, Berlin, Germany, September 8, 2003

A review of literature pertaining to data warehouse implementations over the last eight years has been undertaken. It was found that the views of data warehouse practitioners ...

Dimensional analysis based causal ordering

Conference Proceeding

Shen, Q., Peng, T., & Milne, R. (1998)

Dimensional analysis based causal ordering. In Proceedings of the 13th International Workshop on Qualitative Reasoning, 193-202

This paper presents a novel approach for generating causal dependencies between system variables, from an acausal description of the system behaviour, and for identifying the ...

Representing temporal relationships between events and their effects.

Conference Proceeding

Ma, J., Knight, B., & Peng, T. (1996)

Representing temporal relationships between events and their effects. In Proc. of the 4th Workshop on Temporal Representation and Reasoning, 148-152. doi:10.1109/TIME.1997.600796

Temporal relationships between events and their effects are complex. As the ejjects of a given event, a proposition may change its truth value immediately after the occurrence...