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Tech Report kmi-01-16 Abstract


Literature Review: Information Filtering for Knowledge Management
Techreport ID: kmi-01-16
Date: 2001
Author(s): Nikolaos Nanas
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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.
 
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Multimedia and Information Systems is...


Multimedia and Information Systems
Our research is centred around the theme of Multimedia Information Retrieval, ie, Video Search Engines, Image Databases, Spoken Document Retrieval, Music Retrieval, Query Languages and Query Mediation.

We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.

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