Topical pattern based document modelling and relevance ranking

For traditional information filtering (IF) models, it is often assumed that the documents in one collection are only related to one topic. However, in reality users’ interests can be diverse and the documents in the collection often involve multiple topics. Topic modelling was proposed to generate statistical models to represent multiple topics in a collection of documents, but in a topic model, topics are represented by distributions over words which are limited to distinctively represent the semantics of topics. Patterns are always thought to be more discriminative than single terms and are able to reveal the inner relations between words. This paper proposes a novel information filtering model, Significant matched Pattern-based Topic Model (SPBTM). The SPBTM represents user information needs in terms of multiple topics and each topic is represented by patterns. More importantly, the patterns are organized into groups based on their statistical and taxonomic features, from which the more representative patterns, called Significant Matched Patterns, can be identified and used to estimate the document relevance. Experiments on benchmark data sets demonstrate that the SPBTM significantly outperforms the state-of-the-art models.

Heavy vehicle safety in Oman: Police interviews and heavy vehicle driver survey and focus groups. Third Report of the Heavy Vehicle Safety Research in Oman Project for The Research Council of Oman.

Over the past six months the project has undertaken three key, separate, data collection rounds. Each of these rounds focused on essentially different issues within the broader common construct of heavy vehicle road safety. This document will initially report on a series of two key qualitative data collections rounds. Firstly it will detail findings and report on discussions held in focus groups with 43 heavy vehicle drivers. The second qualitative study involved a series of interviews undertaken with 19 police officers from various levels of command and operations within the Royal Oman Police. The final data collection round reported on in this document is a roadside survey questionnaire undertaken with 400 heavy vehicle drivers.

Liquid Business Process Model Collections

Many organizations realize that increasing amounts of data (“Big Data”) need to be dealt with intelligently in order to compete with other organizations in terms of efficiency, speed and services. The goal is not to collect as much data as possible, but to turn event data into valuable insights that can be used to improve business processes. However, data-oriented analysis approaches fail to relate event data to process models. At the same time, large organizations are generating piles of process models that are disconnected from the real processes and information systems. In this chapter we propose to manage large collections of process models and event data in an integrated manner. Observed and modeled behavior need to be continuously compared and aligned. This results in a “liquid” business process model collection, i.e. a collection of process models that is in sync with the actual organizational behavior. The collection should self-adapt to evolving organizational behavior and incorporate relevant execution data (e.g. process performance and resource utilization) extracted from the logs, thereby allowing insightful reports to be produced from factual organizational data.

Collecting in an urban context: Relationships between collections and space in the home

Collecting has become a popular hobby within Western society, with collectables including anything from ‘bottle tops’ to ‘skyscrapers’. As the nature and size of these collections can impact upon the use of space in the home, the purpose of this study is to explore the relationship between the collections, space in the home and the impacts on others. This qualitative study explores the experiences of 11 Australian collectors, investigating the motivations, practices and adaption techniques used within their urban home environment. The themes of sentimentality, sociability and spatial tensions, including physical, personal and use of space are discussed within the context of their home and family environments. Overall the practice of collecting objects is a complex, varied, sentimental and sociable activity, providing enjoyment, knowledge and friendships. Space can be a central consideration to the practice of collecting as collections shape and are shaped by the available space in a household.

Straightforward data management at QUT

QUT Library Research Support has simplified and streamlined the process of research data management planning, storage, discovery and reuse through collaboration and the use of integrated and tailored online tools, and a simplification of the metadata schema. This poster presents the integrated data management services a QUT, including QUT’s Data Management Planning Tool, Research Data Finder, Spatial Data Finder and Software Finder, and information on the simplified Registry Interchange Format – Collections and Services (RIF-CS) Schema. The QUT Data Management Planning (DMP) Tool was built using the Digital Curation Centre’s DMP Online Tool and modified to QUT’s needs and policies. The tool allows researchers and Higher Degree Research students to plan how to handle research data throughout the active phase of their research. The plan is promoted as a ‘live’ document’ and researchers are encouraged to update it as required. The information entered into the plan can be made private or shared with supervisors, project members and external examiners. A plan is mandatory when requesting storage space on the QUT Research Data Storage Service. QUT’s Research Data Finder is integrated with QUT’s Academic Profiles and the Data Management Planning Tool to create a seamless data management process. This process aims to encourage the creation of high quality rich records which facilitate discovery and reuse of quality data. The Registry Interchange Format – Collections and Services (RIF-CS) Schema that is used in the QUT Research Data Finder was simplified to “RIF-CS lite” to reflect mandatory and optional metadata requirements. RIF-CS lite removed schema fields that were underused or extra to the needs of the users and system. This has reduced the amount of metadata fields required from users and made integration of systems a far more simple process where field content is easily shared across services making the process of collecting metadata as transparent as possible.

Parallel streaming signature EM-tree: A clustering algorithm for web scale applications

The proliferation of the web presents an unsolved problem of automatically analyzing billions of pages of natural language. We introduce a scalable algorithm that clusters hundreds of millions of web pages into hundreds of thousands of clusters. It does this on a single mid-range machine using efficient algorithms and compressed document representations. It is applied to two web-scale crawls covering tens of terabytes. ClueWeb09 and ClueWeb12 contain 500 and 733 million web pages and were clustered into 500,000 to 700,000 clusters. To the best of our knowledge, such fine grained clustering has not been previously demonstrated. Previous approaches clustered a sample that limits the maximum number of discoverable clusters. The proposed EM-tree algorithm uses the entire collection in clustering and produces several orders of magnitude more clusters than the existing algorithms. Fine grained clustering is necessary for meaningful clustering in massive collections where the number of distinct topics grows linearly with collection size. These fine-grained clusters show an improved cluster quality when assessed with two novel evaluations using ad hoc search relevance judgments and spam classifications for external validation. These evaluations solve the problem of assessing the quality of clusters where categorical labeling is unavailable and unfeasible.

Leveraging the repository infrastructure to curate institutional heritage materials, learning objects and data assets

Developing and maintaining a successful institutional repository for research publications requires a considerable investment by the institution. Most of the money is spent on developing the skill-sets of existing staff or hiring new staff with the necessary skills. The return on this investment can be magnified by using this valuable infrastructure to curate collections of other materials such as learning objects, student work, conference proceedings and institutional or local community heritage materials. When Queensland University of Technology (QUT) implemented its repository for research publications (QUT ePrints) over 11 years ago, it was one of the first institutional repositories to be established in Australia. Currently, the repository holds over 29,000 open access research publications and the cumulative total number of full-text downloads for these document now exceeds 16 million. The full-text deposit rate for recently-published peer reviewed papers (currently over 74%) shows how well the repository has been embraced by QUT researchers. The success of QUT ePrints has resulted in requests to accommodate a plethora of materials which are ‘out of scope’ for this repository. QUT Library saw this as an opportunity to use its repository infrastructure (software, technical know-how and policies) to develop and implement a metadata repository for its research datasets (QUT Research Data Finder), a repository for research-related software (QUT Software Finder) and to curate a number of digital collections of institutional and local community heritage materials (QUT Digital Collections). This poster describes the repositories and digital collections curated by QUT Library and outlines the value delivered to the institution, and the wider community, by these initiatives.

Performative digital asset management: To propose a framework and proof of concept model that effectively enables researchers to document, archive and curate their non-traditional research data

This cross disciplinary study was conducted as two research and development projects. The outcome is a multimodal and dynamic chronicle, which incorporates the tracking of spatial, temporal and visual elements of performative practice-led and design-led research journeys. The distilled model provides a strong new approach to demonstrate rigour in non-traditional research outputs including provenance and an 'augmented web of facticity'.

Estimating the under-reporting of road crash injuries to police using multiple linked data collections

The reliance on police data for the counting of road crash injuries can be problematic, as it is well known that not all road crash injuries are reported to police which under-estimates the overall burden of road crash injuries. The aim of this study was to use multiple linked data sources to estimate the extent of under-reporting of road crash injuries to police in the Australian state of Queensland. Data from the Queensland Road Crash Database (QRCD), the Queensland Hospital Admitted Patients Data Collection (QHAPDC), Emergency Department Information System (EDIS), and the Queensland Injury Surveillance Unit (QISU) for the year 2009 were linked. The completeness of road crash cases reported to police was examined via discordance rates between the police data (QRCD) and the hospital data collections. In addition, the potential bias of this discordance (under-reporting) was assessed based on gender, age, road user group, and regional location. Results showed that the level of under-reporting varied depending on the data set with which the police data was compared. When all hospital data collections are examined together the estimated population of road crash injuries was approximately 28,000, with around two-thirds not linking to any record in the police data. The results also showed that the under-reporting was more likely for motorcyclists, cyclists, males, young people, and injuries occurring in Remote and Inner Regional areas. These results have important implications for road safety research and policy in terms of: prioritising funding and resources; targeting road safety interventions into areas of higher risk; and estimating the burden of road crash injuries.

Patient safety and the RCA: A document analysis

This research examined the function of Queensland Health's Root Cause Analysis (RCA) to improve patient safety through an investigation of patient harm events where permanent harm and preventable death, Severity Assessment Code 1, were the outcome of healthcare. Unedited and highly legislated RCAs from across Queensland Health public hospitals from 2009, 2010 and 2011 comprised the data. A document analysis revealed the RCAs opposed organisational policy and dominant theoretical directives. If we accept the prevailing assumption that patient harm is a systemic issue, then the RCA is failing to address harm events in healthcare.

Document timespan normalisation and understanding temporality for clinical records search

Previous qualitative research has highlighted that temporality plays an important role in relevance for clinical records search. In this study, an investigation is undertaken to determine the effect that the timespan of events within a patient record has on relevance in a retrieval scenario. In addition, based on the standard practise of document length normalisation, a document timespan normalisation model that specifically accounts for timespans is proposed. Initial analysis revealed that in general relevant patient records tended to cover a longer timespan of events than non-relevant patient records. However, an empirical evaluation using the TREC Medical Records track supports the opposite view that shorter documents (in terms of timespan) are better for retrieval. These findings highlight that the role of temporality in relevance is complex and how to effectively deal with temporality within a retrieval scenario remains an open question.

Semi-supervised document clustering via loci

Document clustering is one of the prominent methods for mining important information from the vast amount of data available on the web. However, document clustering generally suffers from the curse of dimensionality. Providentially in high dimensional space, data points tend to be more concentrated in some areas of clusters. We take advantage of this phenomenon by introducing a novel concept of dynamic cluster representation named as loci. Clusters’ loci are efficiently calculated using documents’ ranking scores generated from a search engine. We propose a fast loci-based semi-supervised document clustering algorithm that uses clusters’ loci instead of conventional centroids for assigning documents to clusters. Empirical analysis on real-world datasets shows that the proposed method produces cluster solutions with promising quality and is substantially faster than several benchmarked centroid-based semi-supervised document clustering methods.

CCD: Connected Component Descriptor for Robust Mosaicing of Camera-Captured Document Images

We propose a robust method for mosaicing of document images using features derived from connected components. Each connected component is described using the Angular Radial Tran. form (ART). To ensure geometric consistency during feature matching, the ART coefficients of a connected component are augmented with those of its two nearest neighbors. The proposed method addresses two critical issues often encountered in correspondence matching: (i) The stability of features and (ii) Robustness against false matches due to the multiple instances of characters in a document image. The use of connected components guarantees a stable localization across images. The augmented features ensure a successful correspondence matching even in the presence of multiple similar regions within the page. We illustrate the effectiveness of the proposed method on camera captured document images exhibiting large variations in viewpoint, illumination and scale.

The Letter Collections of Anselm of Canterbury

Anselm of Canterbury (1033–1109) was a prolific letter writer. The modern edition of his letter collection comprises more than 600 folio-size pages in print and includes 472 letters, the vast majority of which were sent by him. Our knowledge of Anselm’s letters is derived from collections of his letters, for none of his correspondence survives in its original form of individual letters. There was no one canonical version of the collection, and the extant manuscripts generally differ substantially: the largest medieval manuscript witnesses include over 400 letters, while the smallest contain only a few. We know 38 manuscript witnesses, but no authorial manuscript survives. Certain references in Anselm’s letters reveal, however, that he collected his correspondence on at least two occasions while he was still abbot of Bec, and this study proposes that a third collection was possibly made under his supervision in Christ Church. The third collection also covered Anselm’s Canterbury period. Whether the third collection was authorial or posthumous is unclear. Certain contextual evidence and references in letters would suggest that the collection was authorial. If so, the collection was probably a register book, which was started in c. 1101 at the earliest. There is no positive proof that any of the three surviving minor collections may be authorial. Each of these collections was circulating at a very early stage, however, some probably in Anselm’s lifetime. Moreover, the minor collections seem to have been put together from smaller source units, which possibly originated at Bec. The contents of these units suggest very early and possibly authorial origins: the letters are mainly from Anselm’s years as prior of Bec. The critical edition by F. S. Schmitt represents the current phase in the textual tradition of Anselm’s letter collection. This study demonstrates that the value of the edition is weakened in particular by the way in which Schmitt selected manuscripts for collation, doubtless influenced by the fact that he had not established the structure of the tradition properly. Ultimately it is impossible to undertake systematic research on the letter collection on the basis of Schmitt’s edition.

High-resolution melt-curve analysis of random amplified polymorphic DNA (RAPD-HRM) for the characterisation of pathogenic leptospires: intra-serovar divergence, interserovar convergence, and evidence of attenuation in Leptospira reference collections.

High-resolution melt-curve analysis of random amplified polymorphic DNA (RAPD-HRM) is a novel technology that has emerged as a possible method to characterise leptospires to serovar level. RAPD-HRM has recently been used to measure intra-serovar convergence between strains of the same serovar as well as inter-serovar divergence between strains of different serovars. The results indicate that intra-serovar heterogeneity and inter-serovar homogeneity may limit the application of RAPD-HRM in routine diagnostics. They also indicate that genetic attenuation of aged, high-passage-number isolates could undermine the use of RAPD-HRM or any other molecular technology. Such genetic attenuation may account for a general decrease seen in titres of rabbit hyperimmune antibodies over time. Before RAPD-HRM can be further advanced as a routine diagnostic tool, strains more representative of the wild-type serovars of a given region need to be identified. Further, RAPD-HRM analysis of reference strains indicates that the routine renewal of reference collections, with new isolates, may be needed to maintain the genetic integrity of the collections.