Techniques for intelligent novelty mining
191 p.
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2011
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sg-ntu-dr.10356-469952023-07-04T17:08:27Z Techniques for intelligent novelty mining Tsai, Flora S. Chan Kap Luk School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering 191 p. Intelligent novelty mining addresses the domain-specific problem of mining novel information from text data with specific regard to the user context. Traditional novelty mining focuses on optimizing the retrieval of novel information with a predefined evaluation measure. This tends not be useful in realistic situations where a fixed unit of measure is unable to adapt to the performance requirements of different users. Intelligent novelty mining, on the other hand, aims to balance the technical significance and business concerns to create techniques that are useful in real-world scenarios. This thesis addressed the problem of intelligent novelty mining, which is a big challenge in the data mining and business community. The proposed techniques aim to leverage the use of novelty metrics, novelty decision, and novelty feedback to improve the results of mining new information from text data. DOCTOR OF PHILOSOPHY (EEE) 2011-12-27T05:53:03Z 2011-12-27T05:53:03Z 2010 2010 Thesis Tsai, F. S. (2010). Techniques for intelligent novelty mining. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/46995 10.32657/10356/46995 Nanyang Technological University application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Tsai, Flora S. Techniques for intelligent novelty mining |
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191 p. |
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Chan Kap Luk |
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Chan Kap Luk Tsai, Flora S. |
format |
Theses and Dissertations |
author |
Tsai, Flora S. |
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Tsai, Flora S. |
title |
Techniques for intelligent novelty mining |
title_short |
Techniques for intelligent novelty mining |
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Techniques for intelligent novelty mining |
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Techniques for intelligent novelty mining |
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Techniques for intelligent novelty mining |
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techniques for intelligent novelty mining |
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2011 |
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https://hdl.handle.net/10356/46995 |
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1772828951863885824 |