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Published byRosamund Cox Modified over 6 years ago
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Lecture 7: Knowledge Base Construction: From dark data to insights
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Today’s Lecture Dark data Knowledge base construction (KBC)
Incremental KBC
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Section 1 1. Dark data
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Structure in data is great…
Section 1 Structure in data is great…
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Structure in data is great…
Section 1 Structure in data is great… because computers can understand it
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Structure in data is great…
Section 1 Structure in data is great… because computers can understand it and we can analyze it, obtain insights from it and make better decisions
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Section 1 Sunny days are over
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Section 1 Sunny days are over
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Section 1 Sunny days are over
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Section 1
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Section 1
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2. Knowledge base construction (KBC)
Section 2 2. Knowledge base construction (KBC)
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Personalized medicine
Section 2 Personalized medicine
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Personalized medicine
Section 2 Personalized medicine
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Personalized medicine
Section 2 Personalized medicine
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Personalized medicine
Section 2 Personalized medicine
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Personalized medicine
Section 2 Personalized medicine
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Personalized medicine
Section 2 Personalized medicine
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Section 2 KBC Workflow
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DeepDive is a trained system
Section 2 DeepDive is a trained system
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Section 2
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Section 2 Candidate extraction
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Candidate extraction++
Section 2 Candidate extraction++
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Section 2 Feature extraction
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Section 2 Feature extraction
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Obviate feature engineering
Section 2 Obviate feature engineering
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Section 2 Distant supervision
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DeepDive is a trained system
Section 2 DeepDive is a trained system
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DeepDive is a trained system
Section 2 DeepDive is a trained system
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Probabilistic knowledge engineering
Section 2 Probabilistic knowledge engineering
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Probabilistic knowledge engineering
Section 2 Probabilistic knowledge engineering
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Section 2 Factor graphs
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Probabilistic Inference with Gibbs Sampling
Section 2 Probabilistic Inference with Gibbs Sampling
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Section 3 3. Incremental KBC
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Section 3 Reruns take time
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Section 3
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Section 3
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Section 3 Types of updates
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Incremental Inference: Sampling
Section 3 Incremental Inference: Sampling
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Section 3 Quality over time
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