Automatic detection of new domain-specific words, using document ...

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• Classification procedure – Reflect properties of the material to be processed
• Classification procedure – Reflect properties of the material to be processed ∗ Token overlap between a text and a domain vocabulary ∗ Size of the domain-specific vocabulary ∗ Uniqueness of a certain type for a particular domain ∗ Ratio between recognised and unrecognised tokens
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Automatic detection of new domain-s
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4.3 To compute a score for a certai
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1. Background: updating the DDO •
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1. Background: updating the DDO •
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1.1. Source of new vocabulary • M
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1.3. Prerequisites for the updating
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1.3. Prerequisites for the updating
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2. Data: the DDO Corpus The Corpus
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2. Data: the DDO Corpus The Corpus
Page 23 and 24: 2. Data: the DDO Corpus The Corpus
Page 25 and 26: 2. Data: the DDO Corpus The Corpus
Page 27 and 28: 3. Analysis: deriving domain vocabu
Page 29 and 30: 3.1. Examples: most salient types f
Page 31 and 32: 3.2. Quantitative problems with the
Page 33 and 34: 3.3. Qualitative problems with the
Page 35 and 36: 4. Text classification 4.1. Startin
Page 37 and 38: 4.2. Problems • Highly frequent d
Page 43 and 44: 4.3. To compute a score for a certa
Page 55 and 56: 5. Comparison: determining new word
Page 57 and 58: 5.3. Classification • The text is
Page 63 and 64: 5.6. New sense candidates Type fDDO
Page 65 and 66: 6. Discussion, future, and conclusi
Page 71 and 72: 6.1. Basic decisions - and question
Page 73: 6.1. Basic decisions - and question
Page 77 and 78: • Classification procedure - Refl
Page 79 and 80: • Vocabulary extraction - Based o
Page 81 and 82: 6.2. Testing in progress • Mutual
Page 87 and 88: 6.3. Future work • Domain-specifi
Page 89 and 90: 6.3. Future work • Domain-specifi
Page 91 and 92: 6.4. Conclusion Good: • The mecha
Page 93 and 94: 6.4. Conclusion Good: • The mecha
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