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Lecture 7: Knowledge Base Construction: From dark data to insights

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Presentation on theme: "Lecture 7: Knowledge Base Construction: From dark data to insights"— Presentation transcript:

1 Lecture 7: Knowledge Base Construction: From dark data to insights

2 Today’s Lecture Dark data Knowledge base construction (KBC)
Incremental KBC

3 Section 1 1. Dark data

4 Structure in data is great…
Section 1 Structure in data is great…

5 Structure in data is great…
Section 1 Structure in data is great… because computers can understand it

6 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

7 Section 1 Sunny days are over

8 Section 1 Sunny days are over

9 Section 1 Sunny days are over

10 Section 1

11 Section 1

12 2. Knowledge base construction (KBC)
Section 2 2. Knowledge base construction (KBC)

13 Personalized medicine
Section 2 Personalized medicine

14 Personalized medicine
Section 2 Personalized medicine

15 Personalized medicine
Section 2 Personalized medicine

16 Personalized medicine
Section 2 Personalized medicine

17 Personalized medicine
Section 2 Personalized medicine

18 Personalized medicine
Section 2 Personalized medicine

19 Section 2 KBC Workflow

20 DeepDive is a trained system
Section 2 DeepDive is a trained system

21 Section 2

22 Section 2 Candidate extraction

23 Candidate extraction++
Section 2 Candidate extraction++

24 Section 2 Feature extraction

25 Section 2 Feature extraction

26 Obviate feature engineering
Section 2 Obviate feature engineering

27 Section 2 Distant supervision

28 DeepDive is a trained system
Section 2 DeepDive is a trained system

29 DeepDive is a trained system
Section 2 DeepDive is a trained system

30 Probabilistic knowledge engineering
Section 2 Probabilistic knowledge engineering

31 Probabilistic knowledge engineering
Section 2 Probabilistic knowledge engineering

32 Section 2 Factor graphs

33 Probabilistic Inference with Gibbs Sampling
Section 2 Probabilistic Inference with Gibbs Sampling

34 Section 3 3. Incremental KBC

35 Section 3 Reruns take time

36 Section 3

37 Section 3

38 Section 3 Types of updates

39 Incremental Inference: Sampling
Section 3 Incremental Inference: Sampling

40 Section 3 Quality over time


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