2,503 research outputs found
ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings
This article presents the ReMashed system that recommends learning content from emerging information of a Mash-Up Personal Learning Environment. ReMashed offers advice to find most suitable learning content for individual competence development of lifelong learners. The ReMashed system was initially designed to offer navigational support to lifelong learners in informal learning settings. In this article we want to discuss its ability to be used also in formal learning settings. For this purpose, we discuss the use of two different recommendation approaches for formal and informal learning within ReMashed
ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings
Drachsler, H., Peccau, D., Arts, T., Hutten, E., Rutledge, L., Van Rosmalen, P., Hummel, H. G. K., & Koper, R. (2009). ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings. In F. Wild, M. Kalz, M. Palmér & D. Müller (Eds.), Proceedings of 2nd Workshop Mash-Up Personal Learning Envrionments (MUPPLE'09). Workshop in conjunction with 4th European Conference on Technology Enhanced Learning (EC-TEL 2009): Synergy of Disciplines (pp. 23-30). September, 29, 2009, Nice, France: CEUR workshop proceedings, http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-506 .This article presents the ReMashed system that recommends learning content from emerging information of a Mash-Up Personal Learning Environment. ReMashed offers advice to find most suitable learning content for individual competence development of lifelong learners. The ReMashed system was initially designed to offer navigational support to lifelong learners in informal learning settings. In this article we want to discuss its ability to be used also in formal learning settings. For this purpose, we discuss the use of two different recommendation approaches for formal and informal learning within ReMashed.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
Recommendations based on social links
The goal of this chapter is to give an overview of recent works on the development of social link-based recommender systems and to offer insights on related issues, as well as future directions for research. Among several kinds of social recommendations, this chapter focuses on recommendations, which are based on users’ self-defined (i.e., explicit) social links and suggest items, rather than people of interest. The chapter starts by reviewing the needs for social link-based recommendations and studies that explain the viability of social networks as useful information sources. Following that, the core part of the chapter dissects and examines modern research on social link-based recommendations along several dimensions. It concludes with a discussion of several important issues and future directions for social link-based recommendation research
Fault tolerant architectures for integrated aircraft electronics systems, task 2
The architectural basis for an advanced fault tolerant on-board computer to succeed the current generation of fault tolerant computers is examined. The network error tolerant system architecture is studied with particular attention to intercluster configurations and communication protocols, and to refined reliability estimates. The diagnosis of faults, so that appropriate choices for reconfiguration can be made is discussed. The analysis relates particularly to the recognition of transient faults in a system with tasks at many levels of priority. The demand driven data-flow architecture, which appears to have possible application in fault tolerant systems is described and work investigating the feasibility of automatic generation of aircraft flight control programs from abstract specifications is reported
The Response of Governments and Public Health Agencies to COVID-19 Pandemics on Social Media: A Multi-Country Analysis of Twitter Discourse
During the COVID-19 pandemic, information is being rapidly shared by public health experts and researchers through social media platforms. Whilst government policies were disseminated and discussed, fake news and misinformation simultaneously created a corresponding wave of "infodemics." This study analyzed the discourse on Twitter in several languages, investigating the reactions to government and public health agency social media accounts that share policy decisions and official messages. The study collected messages from 21 official Twitter accounts of governments and public health authorities in the UK, US, Mexico, Canada, Brazil, Spain, and Nigeria, from 15 March to 29 May 2020. Over 2 million tweets in various languages were analyzed using a mixed-methods approach to understand the messages both quantitatively and qualitatively. Using automatic, text-based clustering, five topics were identified for each account and then categorized into 10 emerging themes. Identified themes include political, socio-economic, and population-protection issues, encompassing global, national, and individual levels. A comparison was performed amongst the seven countries analyzed and the United Kingdom (Scotland, Northern Ireland, and England) to find similarities and differences between countries and government agencies. Despite the difference in language, country of origin, epidemiological contexts within the countries, significant similarities emerged. Our results suggest that other than general announcement and reportage messages, the most-discussed topic is evidence-based leadership and policymaking, followed by how to manage socio-economic consequences
Web Data Extraction, Applications and Techniques: A Survey
Web Data Extraction is an important problem that has been studied by means of
different scientific tools and in a broad range of applications. Many
approaches to extracting data from the Web have been designed to solve specific
problems and operate in ad-hoc domains. Other approaches, instead, heavily
reuse techniques and algorithms developed in the field of Information
Extraction.
This survey aims at providing a structured and comprehensive overview of the
literature in the field of Web Data Extraction. We provided a simple
classification framework in which existing Web Data Extraction applications are
grouped into two main classes, namely applications at the Enterprise level and
at the Social Web level. At the Enterprise level, Web Data Extraction
techniques emerge as a key tool to perform data analysis in Business and
Competitive Intelligence systems as well as for business process
re-engineering. At the Social Web level, Web Data Extraction techniques allow
to gather a large amount of structured data continuously generated and
disseminated by Web 2.0, Social Media and Online Social Network users and this
offers unprecedented opportunities to analyze human behavior at a very large
scale. We discuss also the potential of cross-fertilization, i.e., on the
possibility of re-using Web Data Extraction techniques originally designed to
work in a given domain, in other domains.Comment: Knowledge-based System
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