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- Browsing School of Computing and Mathematical Sciences by Issue Date
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Browsing School of Computing and Mathematical Sciences by Issue Date
Now showing items 1-20 of 260
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(Elsevier; 2013)The integration of data mining techniques with data warehousing is gaining popularity due to the fact that both disciplines complement each other in extracting knowledge from large datasets. However, the majority of ... -
(Taylor and Francis; 2012)Research on teaching high school mathematics shows that the topic of percentages often causes learning difficulties. This article describes a method of teaching percentages that the authors used in university bridging ... -
(Science Publications; 2013)Stochastic processes have many useful applications and are taught in several university programmes. Students often encounter difficulties in learning stochastic processes and Markov chains, in particular. In this article ... -
(Taylor & Francis; 2010)The paper introduces a monotony coefficient as a new measure of the monotone dependence in a two-dimensional sample. Some properties of this measure are derived. In particular, it is shown that the absolute value of the ... -
(ASA Publications; 2010)Two improvements in teaching linear regression are suggested. The first is to include the population regression model at the beginning of the topic. The second is to use a geometric approach: to interpret the regression ... -
(Springer; 2013)Near-real-time data warehousing defines how updates from data sources are combined and transformed for storage in a data warehouse as soon as the updates occur. Since these updates are not in warehouse format, they need ...
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(Springer; 2013)New approaches for data provenance and data management (DPDM) are required for mega science projects like the Square Kilometer Array, characterized by extremely large data volume and intense data rates, therefore demanding ... -
(Association for Computing Machinery (ACM); 2013)No abstract. -
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(AUT University; 2013)The paper investigates an approach consisting of data mining techniques namely, rule extraction and prediction, to finding any existing interesting patterns not possible by other means, embedded in meteorological data ... -
(IEEE; 2013)While various key performance limiting factors of IEEE 802.11-based Wi-Fi networks such as wireless protocols, radio propagation environment and signal interference have been studied by many network researchers, the effect ...
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(IEEE; 2013)China has long been an education import nation, so non-commercial and mutually beneficial collaborations between Chinese and Western universities are rare. Nevertheless, the School of Software Engineering at Tongji ... -
(Australian Computer Society (ACS); 2009)Rare itemsets are likely to be of great interest because they often relate to high-impact transactions which may give rise to rules of great practical signi cance. Research into the rare association rule mining problem has ... -
(Australian Computer Society (ACS); 2012)Data mining and data warehousing are two key technologies which have made significant contributions to the field of knowledge discovery in a variety of domains. More recently, the integrated use of traditional data mining ... -
(Australian Computer Society (ACS); 2008)Rare association rule mining has received a great deal of attention in the recent past. In this research, we use transaction clustering as a pre-processing mechanism to generate rare association rules. The basic concept ... -
(Springer Berlin Heidelberg; 2009)Time-series prediction has been a very well researched topic in recent studies. Some popular approaches to this problem are the traditional statistical methods e.g. multiple linear regression and moving average, and neural ... -
(Springer-Verlag; 2008)The behaviour of multiple stock markets can be described within the framework of complex dynamic systems (CDS). Using a global model with the Kalman Filter we are able to extract the dynamic interaction network (DIN) of ... -
A methodology for integrating and exploiting data mining techniques in the design of data warehouses(IEEE; 2010)Data Warehousing and Data Mining are two mature disciplines in their own right. Yet, they have developed largely separate from each other, despite the fact that techniques developed for pattern recognition such as Clustering ... -
(DBLP; 2012)Dynamic symbolic execution has been shown an effective technique for automated test input generation. However, its scalability is limited due to the combinatorial explosion of the path space. We propose to take advantage ... -
(Institute of Electrical and Electronics Engineers (IEEE); 2011)In this paper, we describe the extraction of source code metrics from the Jazz repository and the application of data mining techniques to identify the most useful of those metrics for predicting the success or failure of ... -
(IEEE; 2007)Despite advances in algorithmic design, association rule mining remains problematic from a performance viewpoint when the size of the underlying transaction database is large. The well-known a priori approach, while reducing ...
Now showing items 1-20 of 260