Application of K-tree to document clustering

Digital collections are growing exponentially in size as the information age takes a firm grip on all aspects of society. As a result Information Retrieval (IR) has become an increasingly important area of research. It promises to provide new and more effective ways for users to find information relevant to their search intentions. Document clustering is one of the many tools in the IR toolbox and is far from being perfected. It groups documents that share common features. This grouping allows a user to quickly identify relevant information. If these groups are misleading then valuable information can accidentally be ignored. There- fore, the study and analysis of the quality of document clustering is important. With more and more digital information available, the performance of these algorithms is also of interest. An algorithm with a time complexity of O(n2) can quickly become impractical when clustering a corpus containing millions of documents. Therefore, the investigation of algorithms and data structures to perform clustering in an efficient manner is vital to its success as an IR tool. Document classification is another tool frequently used in the IR field. It predicts categories of new documents based on an existing database of (doc- ument, category) pairs. Support Vector Machines (SVM) have been found to be effective when classifying text documents. As the algorithms for classifica- tion are both efficient and of high quality, the largest gains can be made from improvements to representation. Document representations are vital for both clustering and classification. Representations exploit the content and structure of documents. Dimensionality reduction can improve the effectiveness of existing representations in terms of quality and run-time performance. Research into these areas is another way to improve the efficiency and quality of clustering and classification results. Evaluating document clustering is a difficult task. Intrinsic measures of quality such as distortion only indicate how well an algorithm minimised a sim- ilarity function in a particular vector space. Intrinsic comparisons are inherently limited by the given representation and are not comparable between different representations. Extrinsic measures of quality compare a clustering solution to a “ground truth” solution. This allows comparison between different approaches. As the “ground truth” is created by humans it can suffer from the fact that not every human interprets a topic in the same manner. Whether a document belongs to a particular topic or not can be subjective.

Iteratively specified tree-based regression : theory and trip generation example

Focuses on a study which introduced an iterative modeling method that combines properties of ordinary least squares (OLS) with hierarchical tree-based regression (HTBR) in transportation engineering. Information on OLS and HTBR; Comparison and contrasts of OLS and HTBR; Conclusions.

Response to the apology : Queenslanders reflect : a State Library of Queensland project

On the 13th February 2008 Prime Minister Kevin Rudd made an apology to Australia’s Indigenous Peoples on behalf of the Australian Parliament. The State Library of Queensland (SLQ) with assistance from Queensland University of Technology and Queensland’s Aboriginal and Torres Strait Islander communities, has captured responses to this historic event. ‘Responses to the 2008 Apology’ is a collection of digital stories created as part of this research initiative. Until recently, digital storytelling has not generally been treated as a necessary addition to the research collections of Australian libraries. However, libraries increasingly aim to promote new literacies and active audiences as they seek innovative ways to encourage life-long learning by their users, and digital storytelling is one methodology that can contribute to these goals. The State Library of Queensland is the only Australian State Library to have undertaken a major role in the collection of digital stories. They currently lead the way with their Queensland Stories digital storytelling program. This presentation will report findings and outcomes from this research project.

Reliability evaluations of railway power supplies by fault-tree analysis

High reliability of railway power systems is one of the essential criteria to ensure quality and cost-effectiveness of railway services. Evaluation of reliability at system level is essential for not only scheduling maintenance activities, but also identifying reliability-critical components. Various methods to compute reliability on individual components or regularly structured systems have been developed and proven to be effective. However, they are not adequate for evaluating complicated systems with numerous interconnected components, such as railway power systems, and locating the reliability critical components. Fault tree analysis (FTA) integrates the reliability of individual components into the overall system reliability through quantitative evaluation and identifies the critical components by minimum cut sets and sensitivity analysis. The paper presents the reliability evaluation of railway power systems by FTA and investigates the impact of maintenance activities on overall reliability. The applicability of the proposed methods is illustrated by case studies in AC railways.

Applications on fault tree analysis in railway power supply systems

Fault tree analysis (FTA) is presented to model the reliability of a railway traction power system in this paper. First, the construction of fault tree is introduced to integrate components in traction power systems into a fault tree; then the binary decision diagram (BDD) method is used to evaluate fault trees qualitatively and quantitatively. The components contributing to the reliability of overall system are identified with their relative importance through sensitivity analysis. Finally, an AC traction power system is evaluated by the proposed methods.

Preparing library staff for research support services at QUT

INTRODUCTION: Queensland University of Technology (QUT) Library is partnering with High Performance Computing (HPC) services and the Division of Research and Commercialisation to develop and deliver a range of integrated research support services and systems designed to enhance the research capabilities of the University. Existing and developing research support services include - support for publishing strategies including open access, bibliographic citation and ranking services, research data management, use of online collaboration tools, online survey tools, quantitative and qualitative data analysis, content management and storage solutions. In order to deliver timely and effective research referral and support services, it is imperative that library staff maintain their awareness of, and develop expertise in new eResearch methods and technologies. ---------- METHODS: In 2009/10 QUT Library initiated an online survey for support staff and researchers and a series of focus groups for researchers aimed at gaining a better understanding of current and future eresearch practices and skills. These would better inform the development of a research skills training program and the development of new research support services. The Library and HPC also implemented a program of seminars and workshops designed to introduce key library staff to a broad range of eresearch concepts and technologies. Feedback was obtained after each training session. A number of new services were implemented throughout 2009 and 2010. ---------- RESULTS: Key findings of the survey and focus groups are related to the development of the staff development program. Feedback from program attendees is provided and evaluated. The staff development program is assessed in terms of its success to support the implementation of new research support services. --------- CONCLUSIONS QUT Library has embarked on an ambitious awareness and skills development program to assist Library staff transition a period of rapid change and broadening scope for the Library. Successes and challenges of the program are discussed. A number of recommendations are made in retrospect and also looking forward to the future training needs of Library staff to support the University’s future research goals.

Becoming “Librarian 2.0” : the skills, knowledge, and attributes required by library and information science professionals in a Web 2.0 world (and beyond)

In 2005, Stephen Abram, vice president of Innovation at SirsiDynix, challenged library and information science (LIS) professionals to start becoming “librarian 2.0.” In the last few years, discussion and debate about the “core competencies” needed by librarian 2.0 have appeared in the “biblioblogosphere” (blogs written by LIS professionals). However, beyond these informal blog discussions few systematic and empirically based studies have taken place. This article will discuss a research project that fills this gap. Funded by the Australian Learning and Teaching Council, the project identifies the key skills, knowledge, and attributes required by “librarian 2.0.” Eighty-one members of the Australian LIS profession participated in a series of focus groups. Eight themes emerged as being critical to “librarian 2.0”: technology, communication, teamwork, user focus, business savvy, evidence based practice, learning and education, and personal traits. This article will provide a detailed discussion on each of these themes. The study’s findings also suggest that “librarian 2.0” is a state of mind, and that the Australian LIS profession is undergoing a significant shift in “attitude.”

Australian Library and Information Studies (LIS) researchers' ranking of LIS journals

The paper describes the processes and the outcomes of the ranking of LIS journal titles by Australia’s LIS researchers during 2007-8, firstly through the Australian federal government’s Research Quality Framework (RQF) process and then its replacement, the Excellence in Research for Australia (ERA) initiative. The requirement to rank the journals titles used came from discussions held at the RQF panel meeting held in February 2007 in Canberra, Australia. While it was recognised that the Web of Science (formerly ISI) journal impact approach of journal acceptance for measures of research quality and impact might not work for LIS, it was apparent that this model would be the default if no other ranking of journal titles became apparent. Although an increasing number of LIS and related discipline journals were appearing in the Web of Science listed rankings, the number was few and it was thus decided by the Australian LIS research community to undertake the ranking exercise.

Identification of area-level influences on regions of high cancer incidence in Queensland, Australia : a classification tree approach

Background: Strategies for cancer reduction and management are targeted at both individual and area levels. Area-level strategies require careful understanding of geographic differences in cancer incidence, in particular the association with factors such as socioeconomic status, ethnicity and accessibility. This study aimed to identify the complex interplay of area-level factors associated with high area-specific incidence of Australian priority cancers using a classification and regression tree (CART) approach. Methods: Area-specific smoothed standardised incidence ratios were estimated for priority-area cancers across 478 statistical local areas in Queensland, Australia (1998-2007, n=186,075). For those cancers with significant spatial variation, CART models were used to identify whether area-level accessibility, socioeconomic status and ethnicity were associated with high area-specific incidence. Results: The accessibility of a person’s residence had the most consistent association with the risk of cancer diagnosis across the specific cancers. Many cancers were likely to have high incidence in more urban areas, although male lung cancer and cervical cancer tended to have high incidence in more remote areas. The impact of socioeconomic status and ethnicity on these associations differed by type of cancer. Conclusions: These results highlight the complex interactions between accessibility, socioeconomic status and ethnicity in determining cancer incidence risk.

Library and information science education 2.0: guiding principles and models of best practice. Interview with Sue Reynolds.

In 2005, Stephen Abram, vice president of Innovation at SirsiDynix, challenged library and information science (LIS) professionals to start becoming “librarian 2.0.” In the last few years, discussion and debate about the “core competencies” needed by librarian 2.0 have appeared in the “biblioblogosphere” (blogs written by LIS professionals). However, beyond these informal blog discussions few systematic and empirically based studies have taken place. A project funded by the Australian Learning and Teaching Council fills this gap. The project identifies the key skills, knowledge, and attributes required by “librarian 2.0.” Eighty-one members of the Australian LIS profession participated in a series of focus groups. Eight themes emerged as being critical to “librarian 2.0”: technology, communication, teamwork, user focus, business savvy, evidence based practice, learning and education, and personal traits. Guided by these findings interviews with 36 LIS educators explored the current approaches used within contemporary LIS education to prepare graduates to become “librarian 2.0”. This video presents an example of ‘great practice’ in current LIS educative practice in helping to foster web 2.0 professionals.