Tech Reports
Tech Report kmi-01-16 Abstract
Literature Review: Information Filtering for Knowledge Management
Techreport ID: kmi-01-16
Date: 2001
Author(s): Nikolaos Nanas
It is already realized that we have entered the knowledge era: A time when the economic value of knowledge has become greater than the value of physical products. In this context, Knowledge Management (KM), i.e. the combination of management principles and technology that seeks to improve the performance of individuals and organizations by maintaining and leveraging the value of knowledge assets, has emerged into a managerial megatrend. We present the foundational concepts of Knowledge Management and based on them we argue that information plays an important role to the creation of new knowledge and to its dissemination. The importance of information is also revealed by existing approaches to KM, like knowledge-based systems. We investigate however, the domain of Information Filtering (IF) and its pottential application to KM. The foundations of IF are discussed in conjunction with the more traditional technologies of Information Retrieval and Text Categorization. A number of existing IF systems and agents are then presented from the point of view of KM. We distinguish between systems that have the ability to adapt, systems that have the ability to evolve and finally systems that combine global evolution with local learning. Keywords: Knowledge management, information retrieval, text categorization, term weighting, information filtering, intelligent information agents, adaptation, evolution.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Semantic Web and Knowledge Services is...
Our research in the Semantic Web area looks at the potentials of fusing together advances in a range of disciplines, and applying them in a systemic way to simplify the development of intelligent, knowledge-based web services and to facilitate human access and use of knowledge available on the web. For instance, we are exploring ways in which tnatural language interfaces can be used to facilitate access to data distributed over different repositories. We are also developing infrastructures to support rapid development and deployment of semantic web services, which can be used to create web applications on-the-fly. We are also investigating ways in which semantic technology can support learning on the web, through a combination of knowledge representation support, pedagogical theories and intelligent content aggregation mechanisms. Finally, we are also investigating the Semantic Web itself as a domain of analysis and performing large scale empirical studies to uncover data about the concrete epistemologies which can be found on the Semantic Web. This exciting new area of research gives us concrete insights on the different conceptualizations that are present on the Semantic Web by giving us the possibility to discover which are the most common viewpoints, which viewpoints are mutually inconsistent, to what extent different models agree or disagree, etc...
Our aim is to be at the forefront of both theoretical and practical developments on the Semantic Web not only by developing theories and models, but also by building concrete applications, for a variety of domains and user communities, including KMi and the Open University itself.
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