Issues in learning an ontology from text

Ontology construction for any domain is a labour intensive and complex process. Any methodology that can reduce the cost and increase efficiency has the potential to make a major impact in the life sciences. This paper describes an experiment in ontology construction from text for the Animal Behaviour domain. Our objective was to see how much could be done in a simple and rapid manner using a corpus of journal papers. We used a sequence of text processing steps, and describe the different choices made to clean the input, to derive a set of terms and to structure those terms in a hierarchy. We were able in a very short space of time to construct a 17000 term ontology with a high percentage of suitable terms. We describe some of the challenges, especially that of focusing the ontology appropriately given a starting point of a heterogeneous corpus.

Port community learning needs:analysis and design

The port industry is facing a dramatic wave of changes that have transformed the structure of the industry. Modern seaports are increasingly shifting from a “hardware-based” approach towards “knowhow intensive” configuration. In this context knowledge resources, learning processes and training initiatives increasingly represent key elements to guarantee the quality of service supplied and hence the competitiveness of modern seaport communities. This paper describes the learning needs analysis conducted amongst key port community actors in three ports in the south east of Ireland during 2005 in the context of the I-Sea.Net project. It goes on to describe the learning requirements report and the training design carried out based on this analysis.

Infer user interests via link structure regularization

Learning user interests from online social networks helps to better understand user behaviors and provides useful guidance to design user-centric applications. Apart from analyzing users' online content, it is also important to consider users' social connections in the social Web. Graph regularization methods have been widely used in various text mining tasks, which can leverage the graph structure information extracted from data. Previously, graph regularization methods operate under the cluster assumption that nearby nodes are more similar and nodes on the same structure (typically referred to as a cluster or a manifold) are likely to be similar. We argue that learning user interests from complex, sparse, and dynamic social networks should be based on the link structure assumption under which node similarities are evaluated based on the local link structures instead of explicit links between two nodes. We propose a regularization framework based on the relation bipartite graph, which can be constructed from any type of relations. Using Twitter as our case study, we evaluate our proposed framework from social networks built from retweet relations. Both quantitative and qualitative experiments show that our proposed method outperforms a few competitive baselines in learning user interests over a set of predefined topics. It also gives superior results compared to the baselines on retweet prediction and topical authority identification. © 2014 ACM.

Lecturer’s Web-site and its Role in Distance Learning

Structure of University lecturer’s web-site is suggested. A need for higher education system hyperspace is demonstrated.

Automating Exersises Validation in e-Learning Environments

E-learning is supposing an innovation in teaching, raising from the development of new technologies. It is based in a set of educational resources, including, among others, multimedia or interactive contents accessible through Internet or Intranet networks. A whole spectrum of tools and services support e-learning, some of them include auto-evaluation and automated correction of test-like exercises, however, this sort of exercises are very constrained because of its nature: fixed contents and correct answers suppose a limit in the way teachers may evaluation students. In this paper we propose a new engine that allows validating complex exercises in the area of Data Structures and Algorithms. Correct solutions to exercises do not rely only in how good the execution of the code is, or if the results are same as expected. A set of criteria on algorithm complexity or correctness in the use of the data structures are required. The engine presented in this work covers a wide set of exercises with these characteristics allowing teachers to establish the set of requirements for a solution, and students to obtain a measure on the quality of their solution in the same terms that are later required for exams.

Implementation of Distant Learning Portals based on CASE-technology METAS

The paper describes an approach to the development of software aimed at the creation of distant learning portals integrated with education support and educational institution management systems. The software being developed is based on CASE-technology METAS which is used for the creation of adaptive distributed information systems. This technology allows to dynamically adjust the portal’s structure and portal’s functionality enhancements.

Exploration by Means of Computer Simulation of Nonlinear Hierarchical Structure of Neuronal Memory on the Model of Olfactory Bulb

Results of numerical experiments are introduced. Experiments were carried out by means of computer simulation on olfactory bulb for the purpose of checking of thinking mechanisms conceptual model, introduced in [2]. Key role of quasisymbol neurons in processes of pattern identification, existence of mental view, functions of cyclic connections between symbol and quasisymbol neurons as short-term memory, important role of synaptic plasticity in learning processes are confirmed numerically. Correctness of fundamental ideas put in base of conceptual model is confirmed on olfactory bulb at quantitative level.

The Cascade Neo-Fuzzy Architecture and its Online Learning Algorithm

In the paper learning algorithm for adjusting weight coefficients of the Cascade Neo-Fuzzy Neural Network (CNFNN) in sequential mode is introduced. Concerned architecture has the similar structure with the Cascade-Correlation Learning Architecture proposed by S.E. Fahlman and C. Lebiere, but differs from it in type of artificial neurons. CNFNN consists of neo-fuzzy neurons, which can be adjusted using high-speed linear learning procedures. Proposed CNFNN is characterized by high learning rate, low size of learning sample and its operations can be described by fuzzy linguistic “if-then” rules providing “transparency” of received results, as compared with conventional neural networks. Using of online learning algorithm allows to process input data sequentially in real time mode.

The political discourse and material practice of technology enhanced learning

Technology discloses man’s mode of dealing with Nature, the process of production by which he sustains his life, and thereby also lays bare the mode of formation of his social relations, and of the mental conceptions that flow from them (Marx, 1990: 372) My thesis is a Sociological analysis of UK policy discourse for educational technology during the last 15 years. My framework is a dialogue between the Marxist-based critical social theory of Lieras and a corpus-based Critical Discourse Analysis (CDA) of UK policy for Technology Enhanced Learning (TEL) in higher education. Embedded in TEL is a presupposition: a deterministic assumption that technology has enhanced learning. This conceals a necessary debate that reminds us it is humans that design learning, not technology. By omitting people, TEL provides a vehicle for strong hierarchical or neoliberal, agendas to make simplified claims politically, in the name of technology. My research has two main aims: firstly, I share a replicable, mixed methodological approach for linguistic analysis of the political discourse of TEL. Quantitatively, I examine patterns in my corpus to question forms of ‘use’ around technology that structure a rigid basic argument which ‘enframes’ educational technology (Heidegger, 1977: 38). In a qualitative analysis of findings, I ask to what extent policy discourse evaluates technology in one way, to support a Knowledge Based Economy (KBE) in a political economy of neoliberalism (Jessop 2004, Fairclough 2006). If technology is commodified as an external enhancement, it is expected to provide an ‘exchange value’ for learners (Marx, 1867). I therefore examine more closely what is prioritised and devalued in these texts. Secondly, I disclose a form of austerity in the discourse where technology, as an abstract force, undertakes tasks usually ascribed to humans (Lieras, 1996, Brey, 2003:2). This risks desubjectivisation, loss of power and limits people’s relationships with technology and with each other. A view of technology in political discourse as complete without people closes possibilities for broader dialectical (Fairclough, 2001, 2007) and ‘convivial’ (Illich, 1973) understandings of the intimate, material practice of engaging with technology in education. In opening the ‘black box’ of TEL via CDA I reveal talking points that are otherwise concealed. This allows me as to be reflexive and self-critical through praxis, to confront my own assumptions about what the discourse conceals and what forms of resistance might be required. In so doing, I contribute to ongoing debates about networked learning, providing a context to explore educational technology as a technology, language and learning nexus.

The effectiveness of workplace coaching:A meta-analysis of learning and performance outcomes; scale development; theoretical model of individual differences and longitudinal study

The extant literature on workplace coaching is characterised by a lack of theoretical and empirical understanding regarding the effectiveness of coaching as a learning and development tool; the types of outcomes one can expect from coaching; the tools that can be used to measure coaching outcomes; the underlying processes that explain why and how coaching works and the factors that may impact on coaching effectiveness. This thesis sought to address these substantial gaps in the literature with three linked studies. Firstly, a meta-analysis of workplace coaching effectiveness (k = 17), synthesizing the existing research was presented. A framework of coaching outcomes was developed and utilised to code the studies. Analysis indicated that coaching had positive effects on all outcomes. Next, the framework of outcomes was utilised as the deductive start-point to the development of the scale measuring perceived coaching effectiveness. Utilising a multi-stage approach (n = 201), the analysis indicated that perceived coaching effectiveness may be organised into a six factor structure: career clarity; team performance; work well-being; performance; planning and organizing and personal effectiveness and adaptability. The final study was a longitudinal field experiment to test a theoretical model of individual differences and coaching effectiveness developed in this thesis. An organizational sample of 84 employees each participated in a coaching intervention, completed self-report surveys, and had their job performance rated by peers, direct reports and supervisors (a total of 352 employees provided data on participant performance). The results demonstrate that compared to a control group, the coaching intervention generated a number of positive outcomes. The analysis indicated that coachees’ enthusiasm, intellect and orderliness influenced the impact of coaching on outcomes. Mediation analysis suggested that mastery goal orientation, performance goal orientation and approach motivation in the form of behavioural activation system (BAS) drive, were significant mediators between personality and outcomes. Overall, the findings of this thesis make an original contribution to the understanding of the types of outcomes that can be expected from coaching, and the magnitude of impact coaching has on outcomes. The thesis also provides a tool for reliably measuring coaching effectiveness and a theoretical model to understand the influence of coachee individual differences on coaching outcomes.

Structure of international cooperation in trade, investment and environment

This dissertation analyzes the obstacles against further cooperation in international economic relations. The first essay explains the gradual nature of trade liberalization. I show that existence of asymmetric information between governments provides a sufficient reason for gradualism to exist. Governments prefer starting small to reduce the cost of partner’s betrayal when there is sufficient degree of information asymmetry regarding the partner’s type. Learning about partner’s incentive structure enhances expectations, encouraging governments to increase their current level of cooperation. Specifically, the uninformed government’s subjective belief for the trading partner being good is improved as the partner acts cooperatively. This updated belief, in turn, lowers the subjective probability of future betrayal, enabling further progress in cooperation. The second essay analyzes the relationship between two countries facing two policy dilemmas in an environment with two way goods and capital flows. When issues are independent and countries are symmetric, signing separate agreements for tariffs (Free Trade Agreements-FTA) and for taxes (Tax Treaties-TT) provides the identical level of enforcement as signing a linked agreement. However, linkage can still improve the joint welfare by transferring the slack enforcement power in a case of asymmetric issues or countries. I report non-results in two cases where the policy issues are interconnected due to technological spillover effect of FDI. Moreover, I show that linking the agreements actually reduces enforcement when agreements are linked under a limited punishment rule and policy variables are strategic substitutes. The third essay investigates the welfare/enforcement consequences of linking trade and environmental agreements. In the standard literature, linking the agreements generate non-trivial results only when there is structural relation between the issues. I focus on institutional design of the linkage and show that even if environmental aspects of international trade are negligible linking the agreements might still have some interesting welfare implications under current GATT Rules. Specifically, when traded goods are substitutes in consumption, linking the environmental agreement with trade agreement under the Withdrawal of Equivalent Concession Rule (Article XXVIII) will reduce the enforcement. However, enforcement in environmental issue increases when the same rule is implemented in the absence of linkage.

Laboratory focussed learning of core electronic engineering concepts in the first year of an honours degree programme

In common with most universities teaching electronic engineering in the UK, Aston University has seen a shift in the profile of its incoming students in recent years. The educational background of students has moved away from traditional Alevel maths and science and if anything this variation is set to increase with the introduction of engineering diplomas. Another major change to the circumstances of undergraduate students relates to the introduction of tuition fees in 1998 which has resulted in an increased likelihood of them working during term time. This may have resulted in students tending to concentrate on elements of the course that directly provide marks contributing to the degree classification. In the light of these factors a root and branch rethink of the electronic engineering degree programme structures at Aston was required. The factors taken into account during the course revision were:. Changes to the qualifications of incoming students. Changes to the background and experience of incoming students. Increase in overseas students, some with very limited practical experience. Student focus on work directly leading to marks. Modular compartmentalisation of knowledge. The need for provision of continuous feedback on performance We discuss these issues with specific reference to a 40 credit first year electronic engineering course and detail the new course structure and evaluate the effectiveness of the changes. The new approach appears to have been successful both educationally and with regards to student satisfaction. The first cohort of students from the new course will graduate in 2010 and results from student surveys relating particularly to project and design work will be presented at the conference. © 2009 K Sugden, D J Webb and R P Reeves.

Development of a work-based learning MSc course which incorporates the development and demonstration of professional engineering competence standards

UK engineering standards are regulated by the Engineering Council (EC) using a set of generic threshold competence standards which all professionally registered Chartered Engineers in the UK must demonstrate, underpinned by a separate academic qualification at Masters Level. As part of an EC-led national project for the development of work-based learning (WBL) courses leading to Chartered Engineer registration, Aston University has started an MSc Professional Engineering programme, a development of a model originally designed by Kingston University, and build around a set of generic modules which map onto the competence standards. The learning pedagogy of these modules conforms to a widely recognised experiential learning model, with refinements incorporated from a number of other learning models. In particular, the use of workplace mentoring to support the development of critical reflection and to overcome barriers to learning is being incorporated into the learning space. This discussion paper explains the work that was done in collaboration with the EC and a number of Professional Engineering Institutions, to design a course structure and curricular framework that optimises the engineering learning process for engineers already working across a wide range of industries, and to address issues of engineering sustainability. It also explains the thinking behind the work that has been started to provide an international version of the course, built around a set of globalised engineering competences. © 2010 W J Glew, E F Elsworth.

Argument structure and specific language impairment: retrospect and prospect

This article reflects a collaboration between the Universities of Groningen and Reading of which Frans Zwarts was the promoter. One of the outcomes was a close attention to the learning of various aspects of argument structure by children with specific language impairment (SLI) in Dutch and English. At that time and since, the focus on deficits in grammatical morphology in these children has left verb complementation as something of a syntactic Cinderella. Here we review the findings from our studies in the 1990s. We confirm that children with SLI in both languages have problems with verb specificity, with argument structure alternations and with resultative verb predicates. The very limited number of subsequent studies on verb syntax appear to support our findings. We conclude that this is an area which will repay further scrutiny – it is high time argument structure received an invitation to the ball.

New Advancements of Scalable Statistical Methods for Learning Latent Structures in Big Data

Constant technology advances have caused data explosion in recent years. Accord- ingly modern statistical and machine learning methods must be adapted to deal with complex and heterogeneous data types. This phenomenon is particularly true for an- alyzing biological data. For example DNA sequence data can be viewed as categorical variables with each nucleotide taking four different categories. The gene expression data, depending on the quantitative technology, could be continuous numbers or counts. With the advancement of high-throughput technology, the abundance of such data becomes unprecedentedly rich. Therefore efficient statistical approaches are crucial in this big data era.

Previous statistical methods for big data often aim to find low dimensional struc- tures in the observed data. For example in a factor analysis model a latent Gaussian distributed multivariate vector is assumed. With this assumption a factor model produces a low rank estimation of the covariance of the observed variables. Another example is the latent Dirichlet allocation model for documents. The mixture pro- portions of topics, represented by a Dirichlet distributed variable, is assumed. This dissertation proposes several novel extensions to the previous statistical methods that are developed to address challenges in big data. Those novel methods are applied in multiple real world applications including construction of condition specific gene co-expression networks, estimating shared topics among newsgroups, analysis of pro- moter sequences, analysis of political-economics risk data and estimating population structure from genotype data.