Multi-version documents : A digitisation solution for textual cultural artefacts

Textual cultural heritage artefacts present two serious problems for the encoder: how to record different or revised versions of the same work, and how to encode conflicting perspectives of the text using markup. Both are forms of textual variation, and can be accurately recorded using a multi-version document, based on a minimally redundant directed graph that cleanly separates variation from content.

XML documents clustering using tensor space model - A preliminary study

A hierarchical structure is used to represent the content of the semi-structured documents such as XML and XHTML. The traditional Vector Space Model (VSM) is not sufficient to represent both the structure and the content of such web documents. Hence in this paper, we introduce a novel method of representing the XML documents in Tensor Space Model (TSM) and then utilize it for clustering. Empirical analysis shows that the proposed method is scalable for a real-life dataset as well as the factorized matrices produced from the proposed method helps to improve the quality of clusters due to the enriched document representation with both the structure and the content information.

Overview of the INEX 2010 XML mining track : clustering and classification of XML documents

The XML Document Mining track was launched for exploring two main ideas: (1) identifying key problems and new challenges of the emerging field of mining semi-structured documents, and (2) studying and assessing the potential of Machine Learning (ML) techniques for dealing with generic ML tasks in the structured domain, i.e., classification and clustering of semi-structured documents. This track has run for six editions during INEX 2005, 2006, 2007, 2008, 2009 and 2010. The first five editions have been summarized in previous editions and we focus here on the 2010 edition. INEX 2010 included two tasks in the XML Mining track: (1) unsupervised clustering task and (2) semi-supervised classification task where documents are organized in a graph. The clustering task requires the participants to group the documents into clusters without any knowledge of category labels using an unsupervised learning algorithm. On the other hand, the classification task requires the participants to label the documents in the dataset into known categories using a supervised learning algorithm and a training set. This report gives the details of clustering and classification tasks.

XML documents clustering using Tensor Space Model

The traditional Vector Space Model (VSM) is not able to represent both the structure and the content of XML documents. This paper introduces a novel method of representing XML documents in a Tensor Space Model (TSM) and then utilizing it for clustering. Empirical analysis shows that the proposed method is scalable for large-sized datasets; as well, the factorized matrices produced from the proposed method help to improve the quality of clusters through the enriched document representation of both structure and content information.

Selected new training documents to update user profile

Relevance Feedback (RF) has been proven very effective for improving retrieval accuracy. Adaptive information filtering (AIF) technology has benefited from the improvements achieved in all the tasks involved over the last decades. A difficult problem in AIF has been how to update the system with new feedback efficiently and effectively. In current feedback methods, the updating processes focus on updating system parameters. In this paper, we developed a new approach, the Adaptive Relevance Features Discovery (ARFD). It automatically updates the system's knowledge based on a sliding window over positive and negative feedback to solve a nonmonotonic problem efficiently. Some of the new training documents will be selected using the knowledge that the system currently obtained. Then, specific features will be extracted from selected training documents. Different methods have been used to merge and revise the weights of features in a vector space. The new model is designed for Relevance Features Discovery (RFD), a pattern mining based approach, which uses negative relevance feedback to improve the quality of extracted features from positive feedback. Learning algorithms are also proposed to implement this approach on Reuters Corpus Volume 1 and TREC topics. Experiments show that the proposed approach can work efficiently and achieves the encouragement performance.

Enduring documents : improving the forms, improving the outcomes

Most Australian states have introduced legislation to provide for enduring documents for financial, personal and health care decision making in the event of incapacity. Since the introduction of Enduring Powers of Attorney (EPAs) and Advance Health Directives (AHDs) in Queensland in 1998, concerns have continued to be raised by service providers, professionals and individuals about the uptake, understanding and appropriate use of these documents. In response to these concerns, the Department of Justice and Attorney-General (DJAG) convened a Practical Guardianship Initiatives Working Party. This group identified the limited evidence base available to address these concerns. In 2009, a multidisciplinary research team from the University of Queensland and the Queensland University of Technology was awarded $90,000 from the Legal Practitioners Interest on Trust Account Fund to undertake a review of the current EPA and AHD forms. The goal of the research was to gather data on the content and useability of the forms from the perspectives of a range of stakeholders, particularly those completing the EPA and AHD, witnesses of these documents, attorneys appointed under an EPA, and health professionals involved in the completion of an AHD or dealing with it in a clinical context. The researchers also sought to gather information from the perspective of Aboriginal and Torres Strait Islander (ATSI) individuals as well people from culturally and linguistically diverse (CALD) groups. Although the focus of the research was on the forms and the extent to which the current design, content and format represents a barrier to uptake, in the course of the research, some broader issues were identified which have an impact on the effectiveness of the EPA and AHD in achieving the goals of planning for financial and personal and health care in advance of losing capacity. The data gathered enabled the researchers to achieve the primary goal of the research: to make recommendations to improve the content and useability of the forms which hopefully will lead to an increased uptake and appropriate use of the forms. However, the researchers thought it was important not to ignore broader policy issues that were identified in the course of the research. These broader issues have been highlighted in this Report, and the researchers have responded to them in a variety of ways. For some issues, the researchers have suggested alterations that could be made to the forms to address the particular concerns. For other issues, the researchers have suggested that Government may need to take specific action such as educating the broader community with some attention to strategies that engage particular groups within communities. Other concerns raised can only be dealt with by legislative reform and, in some of these cases, the researchers have identified issues that Government may wish to consider further. We do note, however, that it is beyond the scope of this Report to recommend changes to the law. This three stage mixed methods project aimed to provide systematic evidence from a broad range of stakeholders in regard to: (i) which groups use and do not use these documents and why, (ii) the contribution of the length/complexity/format/language of the forms as barriers to their completion and/or effective use, and (iii) the issues raised by the current documents for witnesses and attorneys. Understanding and use of EPAs and AHDs were generally explored in separate but parallel processes. A purposive sampling strategy included users of the documents as principals and attorneys, and professionals, witnesses and service providers who assist others to execute or use the forms. The first component of this study built on existing knowledge using a Critical Reference Group and material provided by the DJAG Practical Guardianship Initiatives Working Party. This assisted in the development of the data collection tools for subsequent stages. The second component comprised semi-structured interviews and focus groups with a targeted sample of current users of the forms, potential users, witnesses and other professionals to provide in-depth information on critical issues. Outreach to Aboriginal and Torres Strait Islander Elders and individuals and workers with CALD groups ensured a broad sample of potential users of the two documents. Fifty individual interviews and three focus groups were completed. Most interviews and focus groups focused on perceptions of, and experiences with, either the EPA or the AHD form. In the interviews with Indigenous people and the CALD focus groups, however, respondents provided their perceptions and experiences of both documents. In general, these respondents had not used the forms and were responding to the documents made available in the interview or focus group. In total, seventy-seven individuals were involved in interviews or focus groups. The final component comprised on-line surveys for EPA principals, EPA attorneys, AHD principals, witnesses of EPAs and AHDs and medical practitioners with experience of AHDs as nominated and/or treating doctors. The surveys were developed from the initial component and the qualitative analysis of the interview and focus group data. A total of 116 surveys were returned from major cities and regional Queensland. The survey data was analysed descriptively for patterns and trends. It is important to note that the aim of the survey was to gain insight into issues and concerns relating to the documents and not to make generalisations to the broader population.

Enriching XML documents clustering by using concise structure and content

With the growing number of XML documents on theWeb it becomes essential to effectively organise these XML documents in order to retrieve useful information from them. A possible solution is to apply clustering on the XML documents to discover knowledge that promotes effective data management, information retrieval and query processing. However, many issues arise in discovering knowledge from these types of semi-structured documents due to their heterogeneity and structural irregularity. Most of the existing research on clustering techniques focuses only on one feature of the XML documents, this being either their structure or their content due to scalability and complexity problems. The knowledge gained in the form of clusters based on the structure or the content is not suitable for reallife datasets. It therefore becomes essential to include both the structure and content of XML documents in order to improve the accuracy and meaning of the clustering solution. However, the inclusion of both these kinds of information in the clustering process results in a huge overhead for the underlying clustering algorithm because of the high dimensionality of the data. The overall objective of this thesis is to address these issues by: (1) proposing methods to utilise frequent pattern mining techniques to reduce the dimension; (2) developing models to effectively combine the structure and content of XML documents; and (3) utilising the proposed models in clustering. This research first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. A clustering framework with two types of models, implicit and explicit, is developed. The implicit model uses a Vector Space Model (VSM) to combine the structure and the content information. The explicit model uses a higher order model, namely a 3- order Tensor Space Model (TSM), to explicitly combine the structure and the content information. This thesis also proposes a novel incremental technique to decompose largesized tensor models to utilise the decomposed solution for clustering the XML documents. The proposed framework and its components were extensively evaluated on several real-life datasets exhibiting extreme characteristics to understand the usefulness of the proposed framework in real-life situations. Additionally, this research evaluates the outcome of the clustering process on the collection selection problem in the information retrieval on the Wikipedia dataset. The experimental results demonstrate that the proposed frequent pattern mining and clustering methods outperform the related state-of-the-art approaches. In particular, the proposed framework of utilising frequent structures for constraining the content shows an improvement in accuracy over content-only and structure-only clustering results. The scalability evaluation experiments conducted on large scaled datasets clearly show the strengths of the proposed methods over state-of-the-art methods. In particular, this thesis work contributes to effectively combining the structure and the content of XML documents for clustering, in order to improve the accuracy of the clustering solution. In addition, it also contributes by addressing the research gaps in frequent pattern mining to generate efficient and concise frequent subtrees with various node relationships that could be used in clustering.

Practice and procedure : an application under r367 of the Uniform Civil Procedure Rules may be of use in obtaining copies of otherwise unavailable documents held by government agencies.

In Bowenbrae Pty Ltd v Flying Fighters Maintenance and Restoration [2010] QDC 347 Reid DCJ made orders requiring the plaintiffs to make application under the Freedom of Information Act 1982 (Cth) (“the FOI Act”) for documents sought by the defendant.

ACE research briefing paper 002: learning and adaptation in the business creation process

This year marks the completion of data collection for year three (Wave 3) of the CAUSEE study. This report uses data from the first three years and focuses on the process of learning and adaptation in the business creation process. Most start-ups need to change their business model, their product, their marketing plan, their market or something else about the business to be successful. PayPal changed their product at least five times, moving from handheld security, to enterprise apps, to consumer apps, to a digital wallet, to payments between handhelds before finally stumbling on the model that made the a multi-billion dollar company revolving around email-based payments. PayPal is not alone and anecdotes abounds of start-ups changing direction: Sysmantec started as an artificial intelligence company, Apple started selling plans to build computers and Microsoft tried to peddle compilers before licensing an operating system out of New Mexico. To what extent do Australian new ventures change and adapt as their ideas and business develop? As a longitudinal study, CAUSEE was designed specifically to observe development in the venture creation process. In this research briefing paper, we compare development over time of randomly sampled Nascent Firms (NF) and Young Firms(YF), concentrating on the surviving cases. We also compare NFs with YFs at each yearly interval. The 'high potential' over sample is not used in this report.

ACE research briefing paper 003 : international perceptions and aspirations

2010 marked the completion of data collection for year three (Wave 3) of the CAUSEE study. This report uses data from the first three years. Australia's population is noted for its mixed international background. The ABS 2006 census reports showed that almost a quarter of Australian population were born overseas, contributing to a high degree of cultural diversity. This report examines the international background and experience of Australian business founders as well as their aspired and actual participation in international markets. In this research briefing paper, we compare Nascent Firm (NF) and Young Firm (YF) groups and also 'Regular' start-ups in both categories with their High Potential counterparts. When we compare characteristics at one point in time and we compare developments over time. Unless otherwise stated the findings we comment on are 'statistically significant'. That is, there is less than 5 per cent risk that they would appear by chance if there is no true difference in the population form which the samples were drawn.

ACE research briefing paper 004 : emerging and young high potential start-ups

In this report we take a look at what separates high potential emerging and young start-ups from others. We compare the characteristics, intentions and behaviours of start-ups that we judge to be 'high potential' with other start-ups. We utilise the first two years of data from the CAUSEE study. We also compare Australian start-ups with a similar study conduced in the US.

ACE research briefing paper 005: Global Entrepreneurship Monitor (GEM) - Australia 2011 National Report

This report maps the current state of entrepreneurship in Australia using data from the Global Entrepreneurship Monitor (GEM) for the year 2011. Entrepreneurship is regarded as a crucial driver for economic well-being. Entrepreneurial activity in new and established firms drives innovation and creates jobs. Entrepreneurs also fuel competition thereby contributing indirectly to market and productivity growth along with improving competitiveness of the national economy. Given the economic landscape that exists as a result of the global financial crisis (GFC), it is probably more important than ever for us to understand the effects and drivers of entrepreneurial activity and attitudes in Australia. The central finding of this report is that entrepreneurship is certainly alive and well in Australia. With 10.5 per cent of the adult population involved in setting up a new business or owning a newly founded business as measured by the total entrepreneurial activity rate (TEA) in 2011, Australia ranks second only to the United States among the innovation-driven (developed) economies. Compared with 2010 the TEA rate has increased by 2.7 percentage points. Furthermore, in regard to employee entrepreneurial activity (EEA) rate in established firms, Australia ranks above average. According to GEM data, 5 per cent of the adult population is engaged in developing or launching new products, a new business unit or subsidiary for their employer. Further analysis of the GEM data also clearly shows that Australia compares well with other major economies in terms of the ‘quality’ of entrepreneurial activities being pursued. Indeed, it is not only the quantity of entrepreneurs but also the level of their aspirations and business goals that are important drivers for economic growth. On average, for each business started in Australia driven by the lack of alternatives for the founder to generate income from any other source, there are five other businesses started where the founders specifically want to take advantage of a business opportunity that they believe will increase their personal income or independence. With respect to innovativeness, 31 per cent of Australian new businesses offer products or services which they consider to be new to customers or where very few, or in some cases no, other businesses offer the same product or service. Both these indicators are higher than the average for innovation-driven economies. Somewhat below average is the international orientation of Australian entrepreneurs whereby only 12 per cent aim at having a substantial share of customers from international markets. So what drives this high quantity and quality of entrepreneurship in Australia? The analysis of the data suggests it is a combination of both business opportunities and entrepreneurial skills. It seems that around 50 per cent of the Australian population identify opportunities for a start-up venture and believe that they have the necessary skills to start a business. Furthermore, a large majority of the Australian population report that high media attention for entrepreneurship provides successful role models for prospective entrepreneurs. As a result, 12 per cent of our respondents have expressed the intention to start a business within the next three years. These numbers are all well above average when compared to the other major economies. With regard to gender, the GEM survey shows a high proportion of female entrepreneurs. Approximately 8.4 per cent of adult females are actually involved in setting up a business or have recently done so. Although this female TEA rate is slightly down from 2010, Australia ranks second among the innovation-driven economies. This paints a healthy picture of access to entrepreneurial opportunities for Australian women.

The language of optimism : how entrepreneurs sell the sizzle in business plan offer documents

Existing macro level research on the new venture creation process recognises the entrepreneur as a central agent in the process yet generally avoids, at each stage of the process, an examination of the micro level psychological behaviour of the individual entrepreneur. By integrating two theoretical approaches to entrepreneurship research, the psychology of the entrepreneur and the entrepreneurship process, this paper examines, using content analysis, the language used by new venture founders in documents directly linked to their capital raising activity. The study examined the language of 108 offer documents (information memorandum’s) which were divided between 54 new ventures that were successful in raising capital and 54 new ventures that either did not proceed further or were not successful in raising capital through the Australian Small Scale Offerings Board. Specifically, we were interested in examining the level of optimism evident in these narratives given that entrepreneurs have been previously described in the literature as being excessively optimistic.

QUT Para at TREC 2012 Web Track : Word Associations for Retrieving Web Documents

Many existing information retrieval models do not explicitly take into account in- formation about word associations. Our approach makes use of rst and second order relationships found in natural language, known as syntagmatic and paradigmatic associ- ations, respectively. This is achieved by using a formal model of word meaning within the query expansion process. On ad hoc retrieval, our approach achieves statistically sig- ni cant improvements in MAP (0.158) and P@20 (0.396) over our baseline model. The ERR@20 and nDCG@20 of our system was 0.249 and 0.192 respectively. Our results and discussion suggest that information about both syntagamtic and paradigmatic associa- tions can assist with improving retrieval eectiveness on ad hoc retrieval.

Briefing paper on eTextbooks and third party eLearning products and their implications for Australian university libraries

The briefing paper was commissioned by the Council of Australian University Librarians (CAUL) to examine the current picture and evolving role of electronic textbooks (eTextbooks) and third party eLearning products in the academic arena. The study reviews industry trends, identifies the major players and considers the different stakeholder perspectives of eTextbook adoption. Within the context of learning and teaching in the digital age, specific areas of research, policy and practice are highlighted to consider the implications that eTextbooks might have for universities in general and for university libraries in particular. An environmental scan focused on the analysis of current developments and the anticipated future directions of digital learning resources in Australia, as well as in other major English speaking countries such as the United Kingdom and the United States. This research guided the development of key interview questions aimed at examining, at a deeper level, diverse stakeholder perspectives about the roles university libraries can play in the adoption of digital learning content.