A rule based taxonomy of dirty data. (2011)
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 quality. To ensure high quality data, enterprises need to have a process, m... Read More about A rule based taxonomy of dirty data..

An evaluation of name matching techniques. (2011)
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, information retrieval, search engine. In such applications, matching names is one of... Read More about An evaluation of name matching techniques..

Improving data quality in data warehousing applications (2010)
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 data quality. To ensure high quality, enterprises need to have a process,... Read More about Improving data quality in data warehousing applications.