13 results

Multi-Objective Evolutionary Optimisation for Prototype-Based Fuzzy Classifiers

Journal Article
Gu, X., Li, M., Shen, L., Tang, G., Ni, Q., Peng, T., & Shen, Q. (in press)
Multi-Objective Evolutionary Optimisation for Prototype-Based Fuzzy Classifiers. IEEE Transactions on Fuzzy Systems, https://doi.org/10.1109/tfuzz.2022.3214241
Evolving intelligent systems (EISs), particularly, the zero-order ones have demonstrated strong performance on many real-world problems concerning data stream classification, ...

Visualization of Online Datasets

Conference Proceeding
Peng, T., & Downie, C. (2017)
Visualization of Online Datasets. In Proceedings of 15th IEEE/ACIS International Conference on Software Engineering Research, Management and Application (SERA). , (239-246
As computing technology advances, computers are being used to orchestrate and advance wide spectrums of commercial and personal life, an element even more significant as we im...

A comparison of techniques for name matching

Journal Article
Peng, T., Li, L., & Kennedy, J. (2012)
A comparison of techniques for name matching. GSTF journal on computing, 2,
Information explosion is a problem for everyone nowadays. It is a great challenge to all kinds of businesses to maintain high quality of data in their information applications...

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 ...

Towards a Synthetic Data Generator for Matching Decision Trees

Conference Proceeding
Peng, T., & Hanke, F. (2016)
Towards a Synthetic Data Generator for Matching Decision Trees. In Proceedings of the 18th International Conference on Enterprise Information Systems. , (135-141). https://doi.org/10.5220/0005829001350141
It is popular to use real-world data to evaluate or teach data mining techniques. However, there are some disadvantages to use real-world data for such purposes. Firstly, real...

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 ...

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...

An Approach to a Laser-Touchscreen System

Book Chapter
Aizeboje, J., & Peng, T. (2016)
An Approach to a Laser-Touchscreen System. In Enterprise Information Systems; Lecture Notes in Business Information Processing (476-495). Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-319-29133-8_23
As modern day technologies advance, so have different methods in which users can interact with computers. Computers are currently being used in combination with devices like p...

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 ...

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 ...