Granule-based knowledge representation for intra and inter transaction association mining

Abstract With the phenomenal growth of electronic data and information, there are many demands for the development of efficient and effective systems (tools) to perform the issue of data mining tasks on multidimensional databases. Association rules describe associations between items in the same transactions (intra) or in different transactions (inter). Association mining attempts to find interesting or useful association rules in databases: this is the crucial issue for the application of data mining in the real world. Association mining can be used in many application areas, such as the discovery of associations between customers’ locations and shopping behaviours in market basket analysis. Association mining includes two phases. The first phase, called pattern mining, is the discovery of frequent patterns. The second phase, called rule generation, is the discovery of interesting and useful association rules in the discovered patterns. The first phase, however, often takes a long time to find all frequent patterns; these also include much noise. The second phase is also a time consuming activity that can generate many redundant rules. To improve the quality of association mining in databases, this thesis provides an alternative technique, granule-based association mining, for knowledge discovery in databases, where a granule refers to a predicate that describes common features of a group of transactions. The new technique first transfers transaction databases into basic decision tables, then uses multi-tier structures to integrate pattern mining and rule generation in one phase for both intra and inter transaction association rule mining. To evaluate the proposed new technique, this research defines the concept of meaningless rules by considering the co-relations between data-dimensions for intratransaction-association rule mining. It also uses precision to evaluate the effectiveness of intertransaction association rules. The experimental results show that the proposed technique is promising.

Effective pattern taxonomy mining in text documents

Many data mining techniques have been proposed for mining useful patterns in databases. However, how to effectively utilize discovered patterns is still an open research issue, especially in the domain of text mining. Most existing methods adopt term-based approaches. However, they all suffer from the problems of polysemy and synonymy. This paper presents an innovative technique, pattern taxonomy mining, to improve the effectiveness of using discovered patterns for finding useful information. Substantial experiments on RCV1 demonstrate that the proposed solution achieves encouraging performance.

Mining patterns and factors contributing to crash severity on road curves

Road curves are an important feature of road infrastructure and many serious crashes occur on road curves. In Queensland, the number of fatalities is twice as many on curves as that on straight roads. Therefore, there is a need to reduce drivers’ exposure to crash risk on road curves. Road crashes in Australia and in the Organisation for Economic Co-operation and Development(OECD) have plateaued in the last five years (2004 to 2008) and the road safety community is desperately seeking innovative interventions to reduce the number of crashes. However, designing an innovative and effective intervention may prove to be difficult as it relies on providing theoretical foundation, coherence, understanding, and structure to both the design and validation of the efficiency of the new intervention. Researchers from multiple disciplines have developed various models to determine the contributing factors for crashes on road curves with a view towards reducing the crash rate. However, most of the existing methods are based on statistical analysis of contributing factors described in government crash reports. In order to further explore the contributing factors related to crashes on road curves, this thesis designs a novel method to analyse and validate these contributing factors. The use of crash claim reports from an insurance company is proposed for analysis using data mining techniques. To the best of our knowledge, this is the first attempt to use data mining techniques to analyse crashes on road curves. Text mining technique is employed as the reports consist of thousands of textual descriptions and hence, text mining is able to identify the contributing factors. Besides identifying the contributing factors, limited studies to date have investigated the relationships between these factors, especially for crashes on road curves. Thus, this study proposed the use of the rough set analysis technique to determine these relationships. The results from this analysis are used to assess the effect of these contributing factors on crash severity. The findings obtained through the use of data mining techniques presented in this thesis, have been found to be consistent with existing identified contributing factors. Furthermore, this thesis has identified new contributing factors towards crashes and the relationships between them. A significant pattern related with crash severity is the time of the day where severe road crashes occur more frequently in the evening or night time. Tree collision is another common pattern where crashes that occur in the morning and involves hitting a tree are likely to have a higher crash severity. Another factor that influences crash severity is the age of the driver. Most age groups face a high crash severity except for drivers between 60 and 100 years old, who have the lowest crash severity. The significant relationship identified between contributing factors consists of the time of the crash, the manufactured year of the vehicle, the age of the driver and hitting a tree. Having identified new contributing factors and relationships, a validation process is carried out using a traffic simulator in order to determine their accuracy. The validation process indicates that the results are accurate. This demonstrates that data mining techniques are a powerful tool in road safety research, and can be usefully applied within the Intelligent Transport System (ITS) domain. The research presented in this thesis provides an insight into the complexity of crashes on road curves. The findings of this research have important implications for both practitioners and academics. For road safety practitioners, the results from this research illustrate practical benefits for the design of interventions for road curves that will potentially help in decreasing related injuries and fatalities. For academics, this research opens up a new research methodology to assess crash severity, related to road crashes on curves.

Exploration and exploitation : the interplay between knowledge and continuous innovation

In rapidly changing environments, organisations require dynamic capabilities to integrate, build and reconfigure resources and competencies to achieve continuous innovation. Although tangible resources are important to promoting the firm’s ability to act, capabilities fundamentally rest in the knowledge created and accumulated by the firm through human capital, organisational routines, processes, practices and norms. The exploration for new ideas, technologies and knowledge – to one side – and – on the other one – the exploitation of existing and new knowledge is essential for continuous innovation. Firms need to decide how best to allocate their scarce resources for both activities and at the same time build dynamic capabilities to keep up with changing market conditions. This in turn, is influenced by the absorptive capacity of the firm to assimilate knowledge. This paper presents a case study that investigates the sources of knowledge in an engineering firm in Australia, and how it is organised and processed. As information pervades the firm from both internal and external sources, individuals integrate knowledge using both exploration and exploitation approaches. The findings illustrate that absorptive capacity can encourage greater leverage for exploration potential leading to radical innovation; and reconfiguring exploitable knowledge for incremental improvements. This study provides an insight for managers in quest of improving knowledge strategies and continuous innovation. It also makes significant theoretical contributions to the literature through extending the concepts of

How environmental and organizational complexity affects opportunity recognition and exploitation in development projects

Principal Topic: Project structures are often created by entrepreneurs and large corporate organizations to develop new products. Since new product development projects (NPDP) are more often situated within a larger organization, intrapreneurship or corporate entrepreneurship plays an important role in bringing these projects to fruition. Since NPDP often involves the development of a new product using immature technology, we describe development of an immature technology. The Joint Strike Fighter (JSF) F-35 aircraft is being developed by the U.S. Department of Defense and eight allied nations. In 2001 Lockheed Martin won a $19 billion contract to develop an affordable, stealthy and supersonic all-weather strike fighter designed to replace a wide range of aging fighter aircraft. In this research we define a complex project as one that demonstrates a number of sources of uncertainty to a degree, or level of severity, that makes it extremely difficult to predict project outcomes, to control or manage project (Remington & Zolin, Forthcoming). Project complexity has been conceptualized by Remington and Pollock (2007) in terms of four major sources of complexity; temporal, directional, structural and technological complexity (See Figure 1). Temporal complexity exists when projects experience significant environmental change outside the direct influence or control of the project. The Global Economic Crisis of 2008 - 2009 is a good example of the type of environmental change that can make a project complex as, for example in the JSF project, where project managers attempt to respond to changes in interest rates, international currency exchange rates and commodity prices etc. Directional complexity exists in a project where stakeholders' goals are unclear or undefined, where progress is hindered by unknown political agendas, or where stakeholders disagree or misunderstand project goals. In the JSF project all the services and all non countries have to agree to the specifications of the three variants of the aircraft; Conventional Take Off and Landing (CTOL), Short Take Off/Vertical Landing (STOVL) and the Carrier Variant (CV). Because the Navy requires a plane that can take off and land on an aircraft carrier, that required a special variant of the aircraft design, adding complexity to the project. Technical complexity occurs in a project using technology that is immature or where design characteristics are unknown or untried. Developing a plane that can take off on a very short runway and land vertically created may highly interdependent technological challenges to correctly locate, direct and balance the lift fans, modulate the airflow and provide equivalent amount of thrust from the downward vectored rear exhaust to lift the aircraft and at the same time control engine temperatures. These technological challenges make costing and scheduling equally challenging. Structural complexity in a project comes from the sheer numbers of elements such as the number of people, teams or organizations involved, ambiguity regarding the elements, and the massive degree of interconnectedness between them. While Lockheed Martin is the prime contractor, they are assisted in major aspects of the JSF development by Northrop Grumman, BAE Systems, Pratt & Whitney and GE/Rolls-Royce Fighter Engineer Team and innumerable subcontractors. In addition to identifying opportunities to achieve project goals, complex projects also need to identify and exploit opportunities to increase agility in response to changing stakeholder demands or to reduce project risks. Complexity Leadership Theory contends that in complex environments adaptive and enabling leadership are needed (Uhl-Bien, Marion and McKelvey, 2007). Adaptive leadership facilitates creativity, learning and adaptability, while enabling leadership handles the conflicts that inevitably arise between adaptive leadership and traditional administrative leadership (Uhl-Bien and Marion, 2007). Hence, adaptive leadership involves the recognition and opportunities to adapt, while and enabling leadership involves the exploitation of these opportunities. Our research questions revolve around the type or source of complexity and its relationship to opportunity recognition and exploitation. For example, is it only external environmental complexity that creates the need for the entrepreneurial behaviours, such as opportunity recognition and opportunity exploitation? Do the internal dimensions of project complexity, such as technological and structural complexity, also create the need for opportunity recognition and opportunity exploitation? The Kropp, Zolin and Lindsay model (2009) describes a relationship between entrepreneurial orientation (EO), opportunity recognition (OR), and opportunity exploitation (OX) in complex projects, with environmental and organizational contextual variables as moderators. We extend their model by defining the affects of external complexity and internal complexity on OR and OX. ---------- Methodology/Key Propositions: When the environment complex EO is more likely to result in OR because project members will be actively looking for solutions to problems created by environmental change. But in projects that are technologically or structurally complex project leaders and members may try to make the minimum changes possible to reduce the risk of creating new problems due to delays or schedule changes. In projects with environmental or technological complexity project leaders who encourage the innovativeness dimension of EO will increase OR in complex projects. But projects with technical or structural complexity innovativeness will not necessarily result in the recognition and exploitation of opportunities due to the over-riding importance of maintaining stability in the highly intricate and interconnected project structure. We propose that in projects with environmental complexity creating the need for change and innovation project leaders, who are willing to accept and manage risk, are more likely to identify opportunities to increase project effectiveness and efficiency. In contrast in projects with internal complexity a much higher willingness to accept risk will be necessary to trigger opportunity recognition. In structurally complex projects we predict it will be less likely to find a relationship between risk taking and OP. When the environment is complex, and a project has autonomy, they will be motivated to execute opportunities to improve the project's performance. In contrast, when the project has high internal complexity, they will be more cautious in execution. When a project experiences high competitive aggressiveness and their environment is complex, project leaders will be motivated to execute opportunities to improve the project's performance. In contrast, when the project has high internal complexity, they will be more cautious in execution. This paper reports the first stage of a three year study into the behaviours of managers, leaders and team members of complex projects. We conduct a qualitative study involving a Group Discussion with experienced project leaders. The objective is to determine how leaders of large and potentially complex projects perceive that external and internal complexity will influence the affects of EO on OR. ---------- Results and Implications: These results will help identify and distinguish the impact of external and internal complexity on entrepreneurial behaviours in NPDP. Project managers will be better able to quickly decide how and when to respond to changes in the environment and internal project events.

Transaction mining for fraud detection in ERP Systems

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour, and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.

Automation of an underground mining vehicle using reactive navigation and opportunistic localization

This paper describes the implementation of an autonomous navigation system onto a 30 tonne Load-Haul-Dump truck. The control architecture is based on a robust reactive wall-following behaviour. To make it purposeful we provide driving hints derived from an approximate nodal-map. For most of the time, the vehicle is driven with weak localization (odometry). This need only be improved at intersections where decisions must be made - a technique we refer to as opportunistic localization. The truck has achieved full-speed autonomous operation at an artificial test mine, and subsequently, at a operational underground mine.

Autonomous control of underground mining vehicles using reactive navigation

Describes how many of the navigation techniques developed by the robotics research community over the last decade may be applied to a class of underground mining vehicles (LHDs and haul trucks). We review the current state-of-the-art in this area and conclude that there are essentially two basic methods of navigation applicable. We describe an implementation of a reactive navigation system on a 30 tonne LHD which has achieved full-speed operation at a production mine.