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
Social Software is...

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.
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