EPSRC Reference: |
GR/A91364/01 |
Title: |
THE FREEDOM TO FORGET:MULTIMEDIA KNOWLEDGE MANAGEMENT |
Principal Investigator: |
Rueger, Professor S |
Other Investigators: |
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Researcher Co-Investigators: |
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Project Partners: |
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Department: |
Computing |
Organisation: |
Imperial College London |
Scheme: |
Advanced Fellowship (Pre-FEC) |
Starts: |
01 October 1999 |
Ends: |
30 September 2004 |
Value (£): |
251,259
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EPSRC Research Topic Classifications: |
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EPSRC Industrial Sector Classifications: |
Communications |
Creative Industries |
Retail |
No relevance to Underpinning Sectors |
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Related Grants: |
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Panel History: |
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Summary on Grant Application Form |
This research proposal addresses the challenging problem of Multimedia Knowledge Management that naturally arises with increasing storing capacity and the advent of the network age. The main obstacles are given on one hand by the assortment of unstructured information such as images, audio material or free text - now available through, eg, the internet - and on the other hand by the huge variety of the potential information need such as director of a certain movie to other images of a similar landscape . These boundary conditions require flexible, learning and self-evolving algorithms that adapt themselves to the user and to the information need.While multiplied sheer computing power and the co-dependent increasing amount of available digital data have dramatically enlarged the demand for information management (as opposed to simple storage), the development in the fields of Artificial Intelligence, Signal Processing and Natural Language Processing has made the vision of effective Knowledge Management more feasible. We aim to develop a unifying theoretical framework in this interdisciplinary area including freetext, speech, image and video analysis. The main focus will be on ergonomic and high-precision retrieval procedures, whose efficiency will be put to a test by prototype implementations and realistic case studies.The proposer has a strong background in the fields of Statistics, Natural Language Processing, Signal Processing and Artificial Intelligence. In particular, he has worked from 1996 until now in the field of data and text mining. The award of the Advanced Fellowship would allow the proposer to build up an independent research career of international standing within the next five years. This would seem to be a natural stage in the development of his academic career after four years of PhD study and some three years of post-doc research.
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Key Findings |
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Potential use in non-academic contexts |
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Impacts |
Description |
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Summary |
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Date Materialised |
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Sectors submitted by the Researcher |
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Project URL: |
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Further Information: |
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Organisation Website: |
http://www.imperial.ac.uk |