Finding Context Specific Information for e-Community
How can Digital Journals Consume Information Efficiently from the Web, Semantic Web and other Digital Libraries
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In digital environments such as electronic journals, finding context specific and task related information is a big challenge, simply due to the availability of the huge amounts of data. There are some of techniques to provide the intended information to users of digital communities (e-communities). However, all available techniques have some inherent problems. Thus, users are often frustrated. This book presents new techniques for discovering highly relevant resources. The discovered resources are supplied to users based on the users' local context. For a digital journal, the framework contri...
In digital environments such as electronic journals, finding context specific and task related information is a big challenge, simply due to the availability of the huge amounts of data. There are some of techniques to provide the intended information to users of digital communities (e-communities). However, all available techniques have some inherent problems. Thus, users are often frustrated. This book presents new techniques for discovering highly relevant resources. The discovered resources are supplied to users based on the users' local context. For a digital journal, the framework contributes in the following four areas: (i) Finding most related papers from multiple sources, (ii) Discovering and visualizing the relationships between experts, (iii) Linking digital journals with digital libraries maintained by some community leading to serendipitous discoveries of other relevant resources, and (iv) Harvesting pertinent resources from Linked Data. The findings of this researchhave been implemented for a digital journal which is known as Journal of Universal Computer Science step by step since 2007, and are now either in productive or prototype use.
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