Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific sk...
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Search engine users often have clear search tasks hidden behind their queries. Inspired by this, the modern search engines are providing an increasing number of services to help users simplify their key tasks. However...
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Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific sk...
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ISBN:
(纸本)9783885791881
Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. In this paper we specify a formal model for folksonomies, briefly describe our own system BibSonomy, which allows for sharing both bookmarks and publication references, and discuss first steps towards emergent semantics.
Integrating and relating heterogeneous data using inference is one of the cornerstones of semantic technologies and there are a variety of ways in which this may be achieved. Cross source relationships can be automati...
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Ontologies are widely considered as the building blocks of the semantic web, and with them, comes the data interoperability issue. As ontologies are not necessarily always labelled in the same natural language, one wa...
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Point cloud-based large scale place recognition is an important but challenging task for many applications such as Simultaneous Localization and Mapping (SLAM). Taking the task as a point cloud retrieval problem, prev...
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Drawing on the experiences and context of others who have already used a particular resource can greatly facilitate that resource's reuse. Such reuse is essential when the resources in question are digital learnin...
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Drawing on the experiences and context of others who have already used a particular resource can greatly facilitate that resource's reuse. Such reuse is essential when the resources in question are digital learning assets, services and models which are expensive both in terms of time and monetary expenditure to develop and use. When these resources are deployed in personalised settings, where each user may be delivered a tailored sequence of resources that uniquely suits their particular needs, gathering and federating a rich view of how these resources are being used becomes important. In this article we describe an approach to facilitating the federating of contextual usage data, which is compiled over the life cycle of a resource. Given that this data is likely to come from a range of different sources, our approach will need to be able to cope with the high level of heterogeneity expected in terms of its structure, syntax and semantics. We describe how such data may be used to support users in assessing the value of learning resources and facilitating their appropriate reuse.
Auction-based Federated Learning (AFL) is a burgeoning research area. However, existing bidding strategies for AFL data consumers (DCs) primarily focus on maximizing expected accumulated utility, disregarding the more...
The usage of Open Government data (OGD) can enable the government transparency for better governance, increase citizen collaboration, and promote innovation through public service improvement. OGD initiatives involve ...
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Blogs, Wikis, and Social Bookmark Tools have rapidly emerged on the Web. The reasons for their immediate success are that people are happy to share information, and that these tools provide an infrastructure for doing...
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