• A methodology for integrating and exploiting data mining techniques in the design of data warehouses

      Usman, M; Pears, R (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 ...
    • A novel evolving clustering algorithm with polynomial regression for chaotic time-series prediction

      Widiputra, H; Kho, H; Lukas; Pears, R; Kasabov, N (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 ...
    • Accelerating multi dimensional queries in data warehouses

      Pears, R (IGI Global Publishing, 2009)
      Data Warehouses are widely used for supporting decision making. On Line Analytical Processing or OLAP is the main vehicle for querying data warehouses. OLAP operations commonly involve the computation of multidimensional ...
    • Cascade effects of load shedding in coupled networks

      Tauch, S; Liu, W; Pears, R (IEEE, 2013)
      Intricate webs of interlinked critical infrastructures such as electrical grid, telecommunication, and transportation are essential for the minimal functioning of contemporary societies and economies. Advances in Information ...
    • Contextual and concept-based interactive query expansion

      Limbu, D; Pears, R; Connor, AM; MacDonell, S (National Advisory Committee on Computing Qualifications (NACCQ), 2006)
      In this paper, we present a novel approach for contextual and concept based query formulation in web-based information retrieval, which is an on-going PhD project being undertaken at the Software Engineering Research Lab ...
    • Contextual relevance feedback in web information retrieval

      Limbu, DK; Connor, AM; Pears, R; MacDonell, S (Association for Computing Machinery (ACM), 2006)
      In this paper, we present an alternative approach to the problem of contextual relevance feedback in web-based information retrieval. Our approach utilises a rich contextual model that exploits a user's implicit and explicit ...
    • Data stream mining for predicting software build outcomes using source code metrics

      Finlay, J; Pears, R; Connor, AM (Elsevier, 2014)
      Context: Software development projects involve the use of a wide range of tools to produce a software artifact. Software repositories such as source control systems have become a focus for emergent research because they ...
    • Dynamic Interaction Networks in modelling and predicting the behaviour of multiple interactive stock markets

      Widiputra, H; Pears, R; Serguieva, A; Kasabov, N (John Wiley & Sons, 2009)
      The behaviour of multiple stock markets can be described within the framework of complex dynamic systems. A representative technique of the framework is the dynamic interaction network (DIN), recently developed in the ...
    • Evaluating the quality of Drupal software modules

      Denham, B; Pears, R; Connor, AM (World Scientific Publishing, 2018)
      Evaluating software modules for inclusion in a Drupal website is a crucial and complex task that currently requires manual assessment of a number of module facets. This study applied data-mining techniques to identify ...
    • Evolving integrated multi-model framework for on line multiple time series prediction

      Pears, R; Widiputra, H; Kasabov, N (Springer, 2013)
      Time series prediction has been extensively researched in both the statistical and computational intelligence literature with robust methods being developed that can be applied across any given application domain. A much ...
    • FGC: an efficient constraint-based frequent set miner

      Pears, R; Kutty, S (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 ...
    • Improving web information retrieval using shared contexts

      Connor, AM; Limbu, DK; MacDonell, SG; Pears, R (Information Sciences and Computer Engineering, 2010)
      The effective utilisation of a user’s context in improving the performance of web search engines is a subject of intense research interest. In particular, much attention has been directed to the enhancement of queries and ...
    • Improving web search using contextual retrieval

      Limbu, DK; Connor, AM; Pears, R; MacDonell, SG (IEEE Computer Society Press, 2009)
      Contextual retrieval is a critical technique for todaypsilas search engines in terms of facilitating queries and returning relevant information. This paper reports on the development and evaluation of a system designed to ...
    • The incremental Fourier classifier: Leveraging the discrete Fourier transform for classifying high speed data streams

      Kithulgoda, CI; Pears, R; Naeem, MA (Elsevier, 2018)
      Two major performance bottlenecks with decision tree based classifiers in a data stream environment are the depth of the tree and the update overhead of maintaining leaf node statistics on an instance-wise basis to ensure ...
    • Integration of Data Mining and Data Warehousing: a practical methodology

      Usman, M; Pears, R (International Journal of Advancements in Computing Technology (IJACT), 2010)
      The ever growing repository of data in all fields poses new challenges to the modern analytical systems. Real-world datasets, with mixed numeric and nominal variables, are difficult to analyze and require effective visual ...
    • Integration of Data Mining and Data Warehousing: a practical methodology

      Usman, M; Pears, R (Advanced Institute of Convergence IT (AICIT), 2010)
      The ever growing repository of data in all fields poses new challenges to the modern analytical systems. Real-world datasets, with mixed numeric and nominal variables, are difficult to analyze and require effective visual ...
    • Measuring cascade effects in interdependent networks by using effective graph resistance

      Tauch, S; Liu, W; Pears, R (IEEE, 2015)
      Understanding the correlation between the underlie network structure and overlay cascade effects in the interdependent networks is one of major challenges in complex network studies. There are some existing metrics that ...
    • Mining developer communication streams

      Connor, AM; Finlay, J.A.; Pears, R (Academy & Industry Research Collaboration Center (AIRCC) Publishing Corporation, 2014)
      This paper explores the concepts of modelling a software development project as a process that results in the creation of a continuous stream of data. In terms of the Jazz repository used in this research, one aspect of ...
    • Mining recurrent concepts in data streams using the discrete Fourier transform

      Sripirakas, S; Pears, R (arXiv, 2014)
      In this research we address the problem of capturing recurring concepts in a data stream environment. Recurrence capture enables the re-use of previously learned classifiers without the need for re-learning while providing ...
    • Mining software metrics from Jazz

      Finlay, J; Connor, AM; Pears, R (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 ...