Retrieving information from microblog using pattern mining and relevance feedback

Retrieving information from Twitter is always challenging due to its large volume, inconsistent writing and noise. Most existing information retrieval (IR) and text mining methods focus on term-based approach, but suffers from the problems of terms variation such as polysemy and synonymy. This problem deteriorates when such methods are applied on Twitter due to the length limit. Over the years, people have held the hypothesis that pattern-based methods should perform better than term-based methods as it provides more context, but limited studies have been conducted to support such hypothesis especially in Twitter. This paper presents an innovative framework to address the issue of performing IR in microblog. The proposed framework discover patterns in tweets as higher level feature to assign weight for low-level features (i.e. terms) based on their distributions in higher level features. We present the experiment results based on TREC11 microblog dataset and shows that our proposed approach significantly outperforms term-based methods Okapi BM25, TF-IDF and pattern based methods, using precision, recall and F measures.

Investigation of sensitivity based load ranking with composite load model in power system

Load modeling plays an important role in power system dynamic stability assessment. One of the widely used methods in assessing load model impact on system dynamic response is through parametric sensitivity analysis. Load ranking provides an effective measure of such impact. Traditionally, load ranking is based on either static or dynamic load model alone. In this paper, composite load model based load ranking framework is proposed. It enables comprehensive investigation into load modeling impacts on system stability considering the dynamic interactions between load and system dynamics. The impact of load composition on the overall sensitivity and therefore on ranking of the load is also investigated. Dynamic simulations are performed to further elucidate the results obtained through sensitivity based load ranking approach.

Overview of the INEX 2011 relevance feedback track

The INEX 2011 Relevance Feedback track offered a refined approach to the evaluation of Focused Relevance Feedback algorithms through simulated exhaustive user feedback. Run in largely identical fashion to the Relevance Feedback track in INEX 2010[2], we simulated a user-in-the loop by re-using the assessments of ad-hoc retrieval obtained from real users who assess focused ad-hoc retrieval submissions. We present the evaluation methodology, its implementation, and experimental results obtained for four submissions from two participating organisations. As the task and evaluation methods did not change between INEX 2010 and now, explanations of these details from the INEX 2010 version of the track have been repeated verbatim where appropriate.

Adopting relevance feature to learn personalized ontologies

Relevance feature and ontology are two core components to learn personalized ontologies for concept-based retrievals. However, how to associate user native information with common knowledge is an urgent issue. This paper proposes a sound solution by matching relevance feature mined from local instances with concepts existing in a global knowledge base. The matched concepts and their relations are used to learn personalized ontologies. The proposed method is evaluated elaborately by comparing it against three benchmark models. The evaluation demonstrates the matching is successful by achieving remarkable improvements in information filtering measurements.

Matching relevance features with ontological concepts

In order to comprehend user information needs by concepts, this paper introduces a novel method to match relevance features with ontological concepts. The method first discovers relevance features from user local instances. Then, a concept matching approach is developed for matching these features to accurate concepts in a global knowledge base. This approach is significant for the transition of informative descriptor and conceptional descriptor. The proposed method is elaborately evaluated by comparing against three information gathering baseline models. The experimental results shows the matching approach is successful and achieves a series of remarkable improvements on search effectiveness.

The Human Fertilisation and Embryology Act 2008 : restrictions on the creation of “saviour siblings” and the relevance of the harm principle

This paper provides an overview of the regulatory developments in the UK which impact on the use of in vitro fertilization (IVF) and embryo screening techniques for the creation of “saviour siblings.” Prior to the changes implemented under the Human Fertilisation and Embryology Act 2008, this specific use of IVF was not addressed by the legislative framework and regulated only by way of policy issued by the Human Fertilisation and Embryology Authority (HFEA). Following the implementation of the statutory reforms, a number of restrictive conditions are now imposed on the face of the legislation. This paper considers whether there is any justification for restricting access to IVF and pre-implantation tissue typing for the creation of “saviour siblings.” The analysis is undertaken by examining the normative factors that have guided the development of the UK regulatory approach prior to the 2008 legislative reforms. The approach adopted in relation to the “saviour sibling” issue is compared to more general HFEA policy, which has prioritized the notion of reproductive choice and determined that restrictions on access are only justified on the basis of harm considerations.

Multi-criteria ranking and source apportionment of airborne particulate matter

Particulate matter research is essential because of the well known significant adverse effects of aerosol particles on human health and the environment. In particular, identification of the origin or sources of particulate matter emissions is of paramount importance in assisting efforts to control and reduce air pollution in the atmosphere. This thesis aims to: identify the sources of particulate matter; compare pollution conditions at urban, rural and roadside receptor sites; combine information about the sources with meteorological conditions at the sites to locate the emission sources; compare sources based on particle size or mass; and ultimately, provide the basis for control and reduction in particulate matter concentrations in the atmosphere. To achieve these objectives, data was obtained from assorted local and international receptor sites over long sampling periods. The samples were analysed using Ion Beam Analysis and Scanning Mobility Particle Sizer methods to measure the particle mass with chemical composition and the particle size distribution, respectively. Advanced data analysis techniques were employed to derive information from large, complex data sets. Multi-Criteria Decision Making (MCDM), a ranking method, drew on data variability to examine the overall trends, and provided the rank ordering of the sites and years that sampling was conducted. Coupled with the receptor model Positive Matrix Factorisation (PMF), the pollution emission sources were identified and meaningful information pertinent to the prioritisation of control and reduction strategies was obtained. This thesis is presented in the thesis by publication format. It includes four refereed papers which together demonstrate a novel combination of data analysis techniques that enabled particulate matter sources to be identified and sampling site/year ranked. The strength of this source identification process was corroborated when the analysis procedure was expanded to encompass multiple receptor sites. Initially applied to identify the contributing sources at roadside and suburban sites in Brisbane, the technique was subsequently applied to three receptor sites (roadside, urban and rural) located in Hong Kong. The comparable results from these international and national sites over several sampling periods indicated similarities in source contributions between receptor site-types, irrespective of global location and suggested the need to apply these methods to air pollution investigations worldwide. Furthermore, an investigation into particle size distribution data was conducted to deduce the sources of aerosol emissions based on particle size and elemental composition. Considering the adverse effects on human health caused by small-sized particles, knowledge of particle size distribution and their elemental composition provides a different perspective on the pollution problem. This thesis clearly illustrates that the application of an innovative combination of advanced data interpretation methods to identify particulate matter sources and rank sampling sites/years provides the basis for the prioritisation of future air pollution control measures. Moreover, this study contributes significantly to knowledge based on chemical composition of airborne particulate matter in Brisbane, Australia and on the identity and plausible locations of the contributing sources. Such novel source apportionment and ranking procedures are ultimately applicable to environmental investigations worldwide.

Open up the building : architectural relevance of building-users and their participations

As buildings have become more advanced and complex, our ability to understand how they are operated and managed has diminished. Modern technologies have given us systems to look after us but it appears to have taken away our say in how we like our environment to be managed. The aim of this paper is to discuss our research concerning spaces that are sensitive to changing needs and allow building-users to have a certain level of freedom to understand and control their environment. We discuss why, what we call the Active Layer, is needed in modern buildings; how building inhabitants are to interact with it; and the development of interface prototypes to test consequences of having the Active Layer in our environment.

Feasibility of ranking articular cartilage conditions with non-destructive near-infrared spectroscopy with extension to the Mankin grading system

Grading osteoarthritic tissue has, until now, been a laboratory process confined to research activities. This thesis establishes a scientific protocol that extends osteoarthritic tissue ranking to surgical practice. The innovative protocol, which now incorporates the structural degeneration of collagen, enhances the traditional Modified Mankin ranking system, enabling its application to real time decision during surgery. Because it is fast and without time consuming laboratory process, it would potentially enable the cataloguing of tissues in osteoarthritic joints in all compartments of diseased joints during surgery for epistemological study and insight into the manifestation of osteoarthritis across age, gender, occupation, physical activities and race.

A data mining framework for relevance feature discovery

This thesis is a study for automatic discovery of text features for describing user information needs. It presents an innovative data-mining approach that discovers useful knowledge from both relevance and non-relevance feedback information. The proposed approach can largely reduce noises in discovered patterns and significantly improve the performance of text mining systems. This study provides a promising method for the study of Data Mining and Web Intelligence.

Retrieval of health advice on the web: AEHRC at ShARe/CLEF eHealth Evaluation Lab Task 3

This paper details the participation of the Australian e- Health Research Centre (AEHRC) in the ShARe/CLEF 2013 eHealth Evaluation Lab { Task 3. This task aims to evaluate the use of information retrieval (IR) systems to aid consumers (e.g. patients and their relatives) in seeking health advice on the Web. Our submissions to the ShARe/CLEF challenge are based on language models generated from the web corpus provided by the organisers. Our baseline system is a standard Dirichlet smoothed language model. We enhance the baseline by identifying and correcting spelling mistakes in queries, as well as expanding acronyms using AEHRC's Medtex medical text analysis platform. We then consider the readability and the authoritativeness of web pages to further enhance the quality of the document ranking. Measures of readability are integrated in the language models used for retrieval via prior probabilities. Prior probabilities are also used to encode authoritativeness information derived from a list of top-100 consumer health websites. Empirical results show that correcting spelling mistakes and expanding acronyms found in queries signi cantly improves the e ectiveness of the language model baseline. Readability priors seem to increase retrieval e ectiveness for graded relevance at early ranks (nDCG@5, but not precision), but no improvements are found at later ranks and when considering binary relevance. The authoritativeness prior does not appear to provide retrieval gains over the baseline: this is likely to be because of the small overlap between websites in the corpus and those in the top-100 consumer-health websites we acquired.

Superactivation of metal electrode surfaces and its relevance to COads oxidation at fuel cell anodes

The inhibiting effect of COads on platinum-based anodes is a major problem in the development of ambient temperature, polyelectrolyte membrane-type fuel cells. One of the unusual features of the response for the oxidative removal of the species in question is that the response observed for this reaction in the positive sweep is highly dependent on the CO admission potential, for example, when the COads is formed in the Hads region it undergoes oxidation at unusually low potentials. Such behaviour is attributed here to hydrogen activation of the platinum surface, with the result that oxide mediators (and COads oxidation) occurs at an earlier stage of the positive sweep. It is also demonstrated, for both platinum and gold in acid solution, that dramatic premonolayer oxidation responses may be observed following suitable preactivation of the electrode surfaces. It is suggested that the defect state of a solid electrode surface is an important variable whose investigation may yield improved fuel cell anode performance.

Characteristics of nontuberculous mycobacteria from a municipal water distribution system and their relevance to human infections

This thesis documented pathogenic species of nontuberculous mycobacteria in the Brisbane water distribution system. When water and shower aerosol strains were compared with human strains of mycobacteria, the study found that the likelihood of acquiring infection from municipal water was specific for four main species. The method for isolation of mycobacteria from water was refined, followed by sampling from 220 sites across Brisbane. A variety of species (incl 15 pathogens) were identified and genotypically compared to human strains. For M. abscessus and M. lentiflavum, water strains clustered with human strains. Pathogenic strains of M. kansasii were found, though non-pathogenic strains dominated. Waterborne strains of M. fortuitum differed to human strains. Extensive home sampling of 20 patients with NTM disease, supported the theory that the risk of acquiring NTM from water or shower aerosols appears species specific for M. avium, M. kansasii, M. lentiflavum and M. abscessus.

A reciprocal collaborative method using relevance feedback and feature importance

In a people-to-people matching systems, filtering is widely applied to find the most suitable matches. The results returned are either too many or only a few when the search is generic or specific respectively. The use of a sophisticated recommendation approach becomes necessary. Traditionally, the object of recommendation is the item which is inanimate. In online dating systems, reciprocal recommendation is required to suggest a partner only when the user and the recommended candidate both are satisfied. In this paper, an innovative reciprocal collaborative method is developed based on the idea of similarity and common neighbors, utilizing the information of relevance feedback and feature importance. Extensive experiments are carried out using data gathered from a real online dating service. Compared to benchmarking methods, our results show the proposed method can achieve noticeable better performance.

But what makes it doctoral? Taking on the traditionalists : interdisciplinary, practice-led doctoral research in the creative industries - a case study in academic politics, research, rigour and relevance

This paper examines a Doctoral journey of interdisciplinary exploration, explication, examination...and exasperation. In choosing to pursue a practice-led doctorate I had determined from the outset that ‘writing 100,000 words that only two people ever read’, was not something which interested me. Hence, the oft-asked question of ‘what kind of doctorate’ I was engaged in, consistently elicited the response, “a useful one”. In order to satisfy my own imperatives of authenticity and usefulness, my doctoral research had to clearly demonstrate relevance to; productively inform; engage with; and add value to: wider professional field(s) of practice; students in the university courses I teach; and the broader community - not just the academic community. Consequently, over the course of my research, the question, ‘But what makes it Doctoral?’ consistently resounded and resonated. Answering that question, to satisfy not only the traditionalists asking it but, perhaps surprisingly, some academic innovators - and more particularly, myself as researcher - revealed academic/political inconsistencies and issues which challenged both the fundamental assumptions and actuality of practice-led research. This paper examines some of those inconsistencies, issues and challenges and provides at least one possible answer to the question: ‘But what makes it Doctoral?’