The efficiency of corpus-based distributional models for literature-based discovery on large data sets

This paper evaluates the efficiency of a number of popular corpus-based distributional models in performing discovery on very large document sets, including online collections. Literature-based discovery is the process of identifying previously unknown connections from text, often published literature, that could lead to the development of new techniques or technologies. Literature-based discovery has attracted growing research interest ever since Swanson's serendipitous discovery of the therapeutic effects of fish oil on Raynaud's disease in 1986. The successful application of distributional models in automating the identification of indirect associations underpinning literature-based discovery has been heavily demonstrated in the medical domain. However, we wish to investigate the computational complexity of distributional models for literature-based discovery on much larger document collections, as they may provide computationally tractable solutions to tasks including, predicting future disruptive innovations. In this paper we perform a computational complexity analysis on four successful corpus-based distributional models to evaluate their fit for such tasks. Our results indicate that corpus-based distributional models that store their representations in fixed dimensions provide superior efficiency on literature-based discovery tasks.

Implementation of an integrated, technology-based, discovery mode assessment item involving an incubation period to enhance learning outcomes for engineering maths students

In this paper we discuss our current efforts to develop and implement an exploratory, discovery mode assessment item into the total learning and assessment profile for a target group of about 100 second level engineering mathematics students. The assessment item under development is composed of 2 parts, namely, a set of "pre-lab" homework problems (which focus on relevant prior mathematical knowledge, concepts and skills), and complementary computing laboratory exercises which are undertaken within a fixed (1 hour) time frame. In particular, the computing exercises exploit the algebraic manipulation and visualisation capabilities of the symbolic algebra package MAPLE, with the aim of promoting understanding of certain mathematical concepts and skills via visual and intuitive reasoning, rather than a formal or rigorous approach. The assessment task we are developing is aimed at providing students with a significant learning experience, in addition to providing feedback on their individual knowledge and skills. To this end, a noteworthy feature of the scheme is that marks awarded for the laboratory work are primarily based on the extent to which reflective, critical thinking is demonstrated, rather than the amount of CBE-style tasks completed by the student within the allowed time. With regard to student learning outcomes, a novel and potentially critical feature of our scheme is that the assessment task is designed to be intimately linked to the overall course content, in that it aims to introduce important concepts and skills (via individual student exploration) which will be revisited somewhat later in the pedagogically more restrictive formal lecture component of the course (typically a large group plenary format). Furthermore, the time delay involved, or "incubation period", is also a deliberate design feature: it is intended to allow students the opportunity to undergo potentially important internal re-adjustments in their understanding, before being exposed to lectures on related course content which are invariably delivered in a more condensed, formal and mathematically rigorous manner. In our presentation, we will discuss in more detail our motivation and rationale for trailing such a scheme for the targeted student group. Some of the advantages and disadvantages of our approach (as we perceived them at the initial stages) will also be enumerated. In a companion paper, the theoretical framework for our approach will be more fully elaborated, and measures of student learning outcomes (as obtained from eg. student provided feedback) will be discussed.

Developing an IS-Impact decision tool : a literature based design science roadmap

This paper derives from research-in-progress intending both Design Research (DR) and Design Science (DS) outputs; the former a management decision tool based in IS-Impact (Gable et al. 2008) kernel theory; the latter being methodological learnings deriving from synthesis of the literature and reflection on the DR ‘case study’ experience. The paper introduces a generic, detailed and pragmatic DS ‘Research Roadmap’ or methodology, deriving at this stage primarily from synthesis and harmonization of relevant concepts identified through systematic archival analysis of related literature. The scope of the Roadmap too has been influenced by the parallel study aim to undertake DR applying and further evolving the Roadmap. The Roadmap is presented in attention to the dearth of detailed guidance available to novice Researchers in Design Science Research (DSR), and though preliminary, is expected to evolve and gradually be substantiated through experience of its application. A key distinction of the Roadmap from other DSR methods is its breadth of coverage of published DSR concepts and activities; its detail and scope. It represents a useful synthesis and integration of otherwise highly disparate DSR-related concepts.

Many paths lead to discovery : analogical retrieval of cancer therapies

This paper addresses the issue of analogical inference, and its potential role as the mediator of new therapeutic discoveries, by using disjunction operators based on quantum connectives to combine many potential reasoning pathways into a single search expression. In it, we extend our previous work in which we developed an approach to analogical retrieval using the Predication-based Semantic Indexing (PSI) model, which encodes both concepts and the relationships between them in high-dimensional vector space. As in our previous work, we leverage the ability of PSI to infer predicate pathways connecting two example concepts, in this case comprising of known therapeutic relationships. For example, given that drug x TREATS disease z, we might infer the predicate pathway drug x INTERACTS WITH gene y ASSOCIATED WITH disease z, and use this pathway to search for drugs related to another disease in similar ways. As biological systems tend to be characterized by networks of relationships, we evaluate the ability of quantum-inspired operators to mediate inference and retrieval across multiple relations, by testing the ability of different approaches to recover known therapeutic relationships. In addition, we introduce a novel complex vector based implementation of PSI, based on Plate’s Circular Holographic Reduced Representations, which we utilize for all experiments in addition to the binary vector based approach we have applied in our previous research.

Medical semantic similarity with a neural language model

Advances in neural network language models have demonstrated that these models can effectively learn representations of words meaning. In this paper, we explore a variation of neural language models that can learn on concepts taken from structured ontologies and extracted from free-text, rather than directly from terms in free-text. This model is employed for the task of measuring semantic similarity between medical concepts, a task that is central to a number of techniques in medical informatics and information retrieval. The model is built with two medical corpora (journal abstracts and patient records) and empirically validated on two ground-truth datasets of human-judged concept pairs assessed by medical professionals. Empirically, our approach correlates closely with expert human assessors ($\approx$ 0.9) and outperforms a number of state-of-the-art benchmarks for medical semantic similarity. The demonstrated superiority of this model for providing an effective semantic similarity measure is promising in that this may translate into effectiveness gains for techniques in medical information retrieval and medical informatics (e.g., query expansion and literature-based discovery).

Using Wikipedia to improve web service discovery

Building and maintaining software are not easy tasks. However, thanks to advances in web technologies, a new paradigm is emerging in software development. The Service Oriented Architecture (SOA) is a relatively new approach that helps bridge the gap between business and IT and also helps systems remain exible. However, there are still several challenges with SOA. As the number of available services grows, developers are faced with the problem of discovering the services they need. Public service repositories such as Programmable Web provide only limited search capabilities. Several mechanisms have been proposed to improve web service discovery by using semantics. However, most of these require manually tagging the services with concepts in an ontology. Adding semantic annotations is a non-trivial process that requires a certain skill-set from the annotator and also the availability of domain ontologies that include the concepts related to the topics of the service. These issues have prevented these mechanisms becoming widespread. This thesis focuses on two main problems. First, to avoid the overhead of manually adding semantics to web services, several automatic methods to include semantics in the discovery process are explored. Although experimentation with some of these strategies has been conducted in the past, the results reported in the literature are mixed. Second, Wikipedia is explored as a general-purpose ontology. The benefit of using it as an ontology is assessed by comparing these semantics-based methods to classic term-based information retrieval approaches. The contribution of this research is significant because, to the best of our knowledge, a comprehensive analysis of the impact of using Wikipedia as a source of semantics in web service discovery does not exist. The main output of this research is a web service discovery engine that implements these methods and a comprehensive analysis of the benefits and trade-offs of these semantics-based discovery approaches.

A data mining based method for discovery of web services and their compositions

Due to the availability of huge number of web services, finding an appropriate Web service according to the requirements of a service consumer is still a challenge. Moreover, sometimes a single web service is unable to fully satisfy the requirements of the service consumer. In such cases, combinations of multiple inter-related web services can be utilised. This paper proposes a method that first utilises a semantic kernel model to find related services and then models these related Web services as nodes of a graph. An all-pair shortest-path algorithm is applied to find the best compositions of Web services that are semantically related to the service consumer requirement. The recommendation of individual and composite Web services composition for a service request is finally made. Empirical evaluation confirms that the proposed method significantly improves the accuracy of service discovery in comparison to traditional keyword-based discovery methods.

Disclosure, conservatism and the cost of equity capital : a review of the foundation literature

In this review piece, we survey the literature on the cost of equity capital implications of corporate disclosure and conservative accounting policy choice decisions with the principle objective of providing insights into the design and methodological issues, which underlie the empirical investigations. We begin with a review of the analytical studies most typically cited in the empirical research as providing a theoretical foundation. We then turn to consider literature that offers insights into the selection of proxies for each of our points of interest, cost of equity capital, disclosure quality and accounting conservatism. As a final step, we review selected empirical studies to illustrate the relevant evidence found within the literature. Based on our review, we interpret the literature as providing the researcher with only limited direct guidance on the appropriate choice of measure for each of the constructs of interest. Further, we view the literature as raising questions about both the interpretation of empirical findings in the face of measurement concerns and the suitability of certain theoretical arguments to the research setting. Overall, perhaps the message which is most clear is that one of the most controversial and fundamental issues underlying the literature is the issue of the diversifiability or nondiversifiability of information effects.

Self in the City : Young Adult Fiction about New York City after 9/11

This chapter discusses fictional texts set in New York City soon after Septem- ber 11, 2001 (9/11), or whose characters are affected by the attacks on the World Trade Center. Whereas these texts may not have been directly marketed at young adults, they all address ‘youth issues’. Each of the books discussed here contain or are focalized through the eyes of adolescent protagonists. They are all coming-of-age narratives in that the crises within them are usually a result of a catastrophe, taking the characters on journeys of self-discovery, which, once fulfilled, lead them back home.1 As Jerry Griswold (1992) has suggested, coming-of-age stories are especially well suited to the American psyche, and are already familiar to readers of literature based in New York City (the most familiar work being J.D. Salinger’s The Catcher in the Rye). As with other clas- sic American young adult (YA) literature, the journey and homecoming com- monly associated with coming-of-age are often employed in fiction about 9/11. With the key elements of loss and suffering, self-awareness, introspection, and growth, the coming-of-age novel also fulfils agendas common to both litera- ture and politics: the literary journey becomes the nation’s journey.

Mentoring preservice teachers in primary mathematics

A literature-based instrument gathered data about 147 final-year preservice teachers’ perceptions of their mentors’ practices related to primary mathematics teaching. Five factors characterized effective mentoring practices in primary mathematics teaching had acceptable Cronbach alphas, that is, Personal Attributes (mean scale score=3.97, SD [standard deviation]=0.81), System Requirements (mean scale score=2.98, SD=0.96), Pedagogical Knowledge (mean scale score=3.61, SD=0.89), Modelling (mean scale score=4.03, SD=0.73), and Feedback (mean scale score=3.80, SD=0.86) were .91, .74, .94, .89, and .86 respectively. Qualitative data (n=44) investigated mentors’ perceptions of mentoring these preservice teachers, including identification of successful mentoring practices and ways to enhance practices.

Understanding preservice teachers’ predispositions for teaching engineering education in Australian schools.

Engineering education is underrepresented in Australia at the primary, middle school and high school levels. Understanding preservice teachers’ preparedness to be involved in engineering will be important for developing an engineering curriculum. This study administered a literature-based survey to 36 preservice teachers, which gathered data about their perceptions of engineering and their predispositions for teaching engineering. Findings indicated that the four constructs associated with the survey had acceptable Cronbach alpha scores (i.e., personal professional attributes .88, student motivation .91, pedagogical knowledge .91, and fused curricula .89). However, there was no “disagree” or “strongly disagree” response greater than 22% for any of the 25 survey items. Generally, these preservice teachers indicated predispositions for teaching engineering in the middle school. Extensive scaffolding and support with education programs will assist preservice teachers to develop confidence in this field. Governments and education departments need to recognise the importance of engineering education, and universities must take a stronger role in developing engineering education curricula.

Introducing Engineering Education in the Middle School

This paper first describes a new three-year, longitudinal project that is implementing engineering education in three middle schools in Australia (grade levels 7-9). This important domain is untapped in Australia. Hence, as a starting point, we conducted a context analysis to help situate engineering education in a school system. We report on this analysis with respect to findings from one of two literature-based surveys that gathered middle-school student responses in mathematics (n=172) and science (n=166) towards understanding their dispositions for engineering education. ANOVA indicated gender differences for 3 out of 23 items in both mathematics and science. In addition, the majority of students agreed or strongly agreed with 17 of the 23 survey items, however, there were some differences between mathematics and science. We conclude the paper with some recommendations for establishing engineering education in schools, including the development of partnerships among engineering and education faculties, school systems, and industry to develop contemporary engineering resources to support school-level mathematics, science, and technology.

Analysing preservice teachers' potential for implementing engineering education in the middle school

Engineering is pivotal to any country's development. Yet there are insufficient engineers to take up available positions in many countries, including Australia (Engineers Australia, 2008). Engineering education is limited in Australia at the primary, middle and high school levels. One of the starting points for addressing this shortfall lies in preservice teacher education. This study explores second-year preservice teachers' potential to teach engineering in middle school, following their engagement with engineering concepts in their science curriculum unit and their teaching of engineering activities to Year 7 students. Using a literature-based pretest-posttest survey, items were categorised into four constructs (ie. personal professional attributes, student motivation, pedagogical knowledge and fused curricula). Results indicated that the preservice teachers' responses had not changed for instilling positive attitudes (88%) and accepting advice from colleagues (94%). However, there was statistical significance with 9 of the 25 survey items (p<0.05) after the preservice teachers' involvement in engineering activities. Fusing engineering education with other subjects, such as mathematics and science, is an essential first step in promoting preservice teachers' potential to implement engineering education in the middle school.

Towards a new employment relationship model

Purpose – The purpose of this study is to examine and extend Noer’s theoretical model of the new employment relationship. Design/methodology/approach – Case study methodology is used to scrutinise the model. The results of a literature-based survey on the elements underpinning the five values in the model are analysed from dual perspectives of individual and organization using a multi-source assessment instrument. A schema is developed to guide and inform a series of focus group discussions from an analysis of the survey data. Using content analysis, the transcripts from the focus group discussions are evaluated using the model’s values and their elements. The transcripts are also reviewed for implicit themes. The case studied is Flight Centre Limited, an Australian-based international retail travel company. Findings – Using this approach, some elements of the five values in Noer’s model are identified as characteristic of the company’s psychological contract. Specifically, to some extent, the model’s values of flexible deployment, customer focus, performance focus, project-based work, and human spirit and work can be applied in this case. A further analysis of the transcripts validates three additional values in the psychological contract literature: commitment; learning and development; and open information. As a result of the findings, Noer’s model is extended to eight values. Research limitations/implications – The study offers a research-based model of the new employment relationship. Since generalisations from the case study findings cannot be applied directly to other settings, the opportunity to test this model in a variety of contexts is open to other researchers. Originality/value – In practice, the methodology used is a unique process for benchmarking the psychological contract. The process may be applied in other business settings. By doing so, organization development professionals have a consulting framework for comparing an organization’s dominant psychological contract with the extended model presented here.