User-centred ontology learning for knowledge management

Automatic ontology building is a vital issue in many fields where they are currently built manually. This paper presents a user-centred methodology for ontology construction based on the use of Machine Learning and Natural Language Processing. In our approach, the user selects a corpus of texts and sketches a preliminary ontology (or selects an existing one) for a domain with a preliminary vocabulary associated to the elements in the ontology (lexicalisations). Examples of sentences involving such lexicalisation (e.g. ISA relation) in the corpus are automatically retrieved by the system. Retrieved examples are validated by the user and used by an adaptive Information Extraction system to generate patterns that discover other lexicalisations of the same objects in the ontology, possibly identifying new concepts or relations. New instances are added to the existing ontology or used to tune it. This process is repeated until a satisfactory ontology is obtained. The methodology largely automates the ontology construction process and the output is an ontology with an associated trained leaner to be used for further ontology modifications.

Engaging tutors in using e-repositories for learning and teaching

Universities which set up online repositories for the management of learning and teaching resources commonly find that uptake is poor. Tutors are often reluctant to upload their materials to e-repositories, even though the same tutors are happy to upload resources to the virtual learning environment (e.g. Blackboard, Moodle, Sakai) and happy to upload their research papers to the university’s research publications repository. The paper reviews this phenomenon and suggests constructive ways in which tutors can be encouraged to engage with an e-repository. The authors have recently completed a major project “Developing Repositories at Worcester” which is part of a group of similar projects in the UK. The paper includes the feedback and the lessons learned from these projects, based on the publications and reports they have produced. They cover ways of embedding repository use into institutional working practice, and give examples of different types of repository designed to meet the needs of those using different kinds of learning and teaching resources. As well as this specific experience, the authors summarise some of the main findings from UK publications, in particular the December 2008 report of Joint Information Systems Committee: Good intentions: improving the evidence base in support of sharing learning materials and Online Innovation in Higher Education, Ron Cooke’s report to a UK government initiative on the future of Higher Education. The issues covered include the development of Web 2.0 style repositories rather than conventionally structured ones, the use of tags rather than metadata, the open resources initiative, the best use for conventional repositories, links to virtual learning environments, and the processes for the management and support of repositories within universities. In summary the paper presents an optimistic, constructive view of how to embed the use of e-repositories into the working practices of university tutors. Equally, the authors are aware of the considerable difficulties in making progress and are realistic about what can be achieved. The paper uses evidence and experience drawn from those working in this field to suggest a strategic vision in which the management of e-learning resources is productive, efficient and meets the needs of both tutors and their students.

Imagery in multi-modal object learning

Spatial objects may not only be perceived visually but also by touch. We report recent experiments investigating to what extent prior object knowledge acquired in either the haptic or visual sensory modality transfers to a subsequent visual learning task. Results indicate that even mental object representations learnt in one sensory modality may attain a multi-modal quality. These findings seem incompatible with picture-based reasoning schemas but leave open the possibility of modality-specific reasoning mechanisms.

Diversifying into technical clothing manufacture as entrepreneurial learning:a situated learning theory perspective

Purpose - The purpose of this paper is to demonstrate analytically how entrepreneurial action as learning relating to diversifying into technical clothing - i.e. a high-value manufacturing sector - can take place. This is particularly relevant to recent discussion and debate in academic and policy-making circles concerning the survival of the clothing manufacture industry in developed industrialised countries. Design/methodology/approach - Using situated learning theory (SLT) as the major analytical lens, this case study examines an episode of entrepreneurial action relating to diversification into a high-value manufacturing sector. It is considered on instrumentality grounds, revealing wider tendencies in the management of knowledge and capabilities requisite for effective entrepreneurial action of this kind. Findings - Boundary events, brokers, boundary objects, membership structures and inclusive participation that addresses power asymmetries are found to be crucial organisational design elements, enabling the development of inter- and intracommunal capacities. These together constitute a dynamic learning capability, which underpins entrepreneurial action, such as diversification into high-value manufacturing sectors. Originality/value - Through a refinement of SLT in the context of entrepreneurial action, the paper contributes to an advancement of a substantive theory of managing technological knowledge and capabilities for effective diversification into high-value manufacturing sectors. Copyright © 2014 Emerald Group Publishing Limited. All rights reserved.

Learning to be different:heterogeneity and efficiency in distributed smart camera networks

In this paper we study the self-organising behaviour of smart camera networks which use market-based handover of object tracking responsibilities to achieve an efficient allocation of objects to cameras. Specifically, we compare previously known homogeneous configurations, when all cameras use the same marketing strategy, with heterogeneous configurations, when each camera makes use of its own, possibly different marketing strategy. Our first contribution is to establish that such heterogeneity of marketing strategies can lead to system wide outcomes which are Pareto superior when compared to those possible in homogeneous configurations. However, since the particular configuration required to lead to Pareto efficiency in a given scenario will not be known in advance, our second contribution is to show how online learning of marketing strategies at the individual camera level can lead to high performing heterogeneous configurations from the system point of view, extending the Pareto front when compared to the homogeneous case. Our third contribution is to show that in many cases, the dynamic behaviour resulting from online learning leads to global outcomes which extend the Pareto front even when compared to static heterogeneous configurations. Our evaluation considers results obtained from an open source simulation package as well as data from a network of real cameras. © 2013 IEEE.