Application of text mining in analysing road crashes for road asset management

Traffic safety is a major concern world-wide. It is in both the sociological and economic interests of society that attempts should be made to identify the major and multiple contributory factors to those road crashes. This paper presents a text mining based method to better understand the contextual relationships inherent in road crashes. By examining and analyzing the crash report data in Queensland from year 2004 and year 2005, this paper identifies and reports the major and multiple contributory factors to those crashes. The outcome of this study will support road asset management in reducing road crashes.

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.

View from a bridge : what makes a musical city

The attention paid by the British music press in 1976 to the release of The Saints first single “I’m Stranded” was the trigger for a commercial and academic interest in the Brisbane music scene which still has significant energy. In 2007, Brisbane was identifed by Billboard Magazine as a “hot spot” of independent music. A place to watch. Someone turned a torch on this town, had a quick look, moved on. But this town has always had music in it. Some of it made by me. So, I’m taking this connection of mine, and working it into a contextual historical analysis of the creative lives of Brisbane musicians. I will be interviewing a number of Brisbane musicians. These interviews have begun, and will continue to be be conducted in 2011/2012. I will ask questions and pursue memories that will encompass family, teenage years, siblings, the suburbs, the city, venues, television and radio; but then widen to welcome the river, the hills and mountains, foes and friends, beliefs and death. The wider research will be a contextual historical analysis of the creative lives of Brisbane musicians. It will explore the changing nature of their work practices over time and will consider the notion, among other factors, of ‘place’ in both their creative practice and their creative output. It will also examine how the presence of the practitioners and their work is seen to contribute to the cultural life of the city and the creative lives of its citizens into the future. This paper offers an analysis of this last notion: how does this city see its music-makers? In addition to the interviews, over 300 Brisbane musicians were surveyed in September 2009 as part of a QUT-initiated recorded music event (BIGJAM). Their responses will inform the production of this paper.

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.

`Getting the city right' : the city as crucible for social reform

The connection between social reform and urban management is evident throughout the history of the city. This article maps out how ideas about social reform and social housing were established historically, during the development of the nineteenth century city. The second part examines contemporary shifts in thinking about homelessness through a case study of two Brisbane City Council initiatives in Brisbane: The Homeless Shelter Trial and Footprints along Kurilpa.

Sounds from the empty city : a practice-led case study in the confluence of music, narrative and emotion

The creative practice: the adaptation of picture book The Empty City (Megarrity/Oxlade, Hachette 2007) into an innovative, interdisciplinary performance for children which combines live performance, music, projected animation and performing objects. The researcher, in the combined roles of writer/composer proposes deliberate experiments in music, narrative and emotion in the various drafts of the adaptation, and tests them in process and performance product. A particular method of composing music for live performance is tested in against the emergent needs of a collaborative, intermedial process. The unpredictable site of research means that this project is both looking to address both pre-determined and emerging points of inquiry. This analysis (directed by audience reception) finds that critical incidents of intermediality between music, narrative, action and emotion translate directly into highlights of the performance.

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.