Unsupervised, Efficient and Semantic Expertise Retrieval

We introduce an unsupervised discriminative model for the task of retrieving experts in online document collections. We exclusively employ textual evidence and avoid explicit feature engineering by learning distributed word representations in an unsupervised way. We compare our model to state-of-the-art unsupervised statistical vector space and probabilistic generative approaches. Our proposed log-linear model achieves the retrieval performance levels of state-of-the-art document-centric methods with the low inference cost of so-called profile-centric approaches. It yields a statistically significant improved ranking over vector space and generative models in most cases, matching the performance of supervised methods on various benchmarks. That is, by using solely text we can do as well as methods that work with external evidence and/or relevance feedback. A contrastive analysis of rankings produced by discriminative and generative approaches shows that they have complementary strengths due to the ability of the unsupervised discriminative model to perform semantic matching.Comment: WWW2016, Proceedings of the 25th International Conference on World Wide Web. 201

Can acquisition of expertise be supported by technology?

Professional trainees in the workplace are increasingly required to demonstrate specific standards of competence. Yet, empirical evidence of how professionals acquire competence in practice is lacking. The danger, then, is that efforts to support learning processes may be misguided. We hypothesised that a systemic view of how expertise is acquired would support more timely and appropriate development of technology to support workplace learning. The aims of this study were to provide an empirically based understanding of workplace learning and explore how learning could be facilitated through suitable application of technology. We have used the medical specialist trainee as an exemplar of how professionals acquire expertise within a complex working environment. We describe our methodological approach, based on the amalgam of systems analysis and qualitative research methods. We present the development of a framework for analysis and early findings from qualitative data analysis. Based on our findings so far, we present a tentative schema representing how technology can support learning with suggestions for the types of technology that could be used

Recommendation domains for pond aquaculture

This publication introduces the methods and results of a research project that has developed a set of decision-support tools to identify places and sets of conditions for which a particular target aquaculture technology is considered feasible and therefore good to promote. The tools also identify the nature of constraints to aquaculture development and thereby shed light on appropriate interventions to realize the potential of the target areas. The project results will be useful for policy planners and decision makers in national, regional and local governments and development funding agencies, aquaculture extension workers in regional and local governments, and researchers in aquaculture systems and rural livelihoods. (Document contains 40 pages

Lifelong guidance policy and practice in the EU

A study on lifelong guidance (LLG) policy and practice in the EU focusing on trends, challenges and opportunities. Lifelong guidance aims to provide career development support for individuals of all ages, at all career stages. It includes careers information, advice, counselling, assessment of skills and mentoring

Social support system in learning network for lifelong learners:a conceptual framework

Nadeem, D., Stoyanov, S., & Koper, R. (2009). Social support system in learning network for lifelong learners: A Conceptual framework [Special issue]. International Journal of Continuing Engineering Education and Life-Long Learning, 19(4/5/6), 337-351.Learning Networks are favorable model for supporting self-directed learning for lifelong learners. Learners can themselves decide about their learning plans to learn at their own pace irrespective of place and time. However, such learners remain hidden from others in the Learning Network., which makes their learning detrimental and less effective. Bringing learners together would benefit them in sharing each others expertise and learn effectively by collaboration. We propose to tackle the problem of finding people in learning networks by developing a Social Support System (SoSuSy) prototype. This position paper presents a conceptual framework for designing SoSuSy in a Learning Network. Such a system connects the learner with other learners who are dealing with similar problem by using their combined skills and to increase their social interaction. We propose by using people’s profile on social network and the public text content they create (blogs and book-marking) supported by web 2.0 applications, to enhance the search for finding suitable people who match in their interests, competence and tasks. We present an informal learning scenario to justify the need for such a system in online distributed Learning Network.The work on this publication has been sponsored by the TENCompetence Integrated Project that is funded by the European Commission's 6th Framework Programme, priority IST/Technology Enhanced Learning. Contract 027087 [http://www.tencompetence.org

What young people want from health-related online resources: a focus group study

The growth of the Internet as an information source about health, particularly amongst young people, is well established. The aim of this study was to explore young people's perceptions and experiences of engaging with health-related online content, particularly through social media websites. Between February and July 2011 nine focus groups were facilitated across Scotland with young people aged between 14 and 18 years. Health-related user-generated content seems to be appreciated by young people as a useful, if not always trustworthy, source of accounts of other people's experiences. The reliability and quality of both user-generated content and official factual content about health appear to be concerns for young people, and they employ specialised strategies for negotiating both areas of the online environment. Young people's engagement with health online is a dynamic area for research. Their perceptions and experiences of health-related content seem based on their wider familiarity with the online environment and, as the online environment develops, so too do young people's strategies and conventions for accessing it