Knowledge for/from People for/from Computers

author: Michael Witbrock, Cycorp Europe
published: Dec. 23, 2011,   recorded: November 2011,   views: 144
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Slides

Slides
0:00 Knowledge for / from People for / from Computers
0:49 What’s all this about people and computers
5:30 Use Case: Semantic Patient Records
6:56 In use at the Cleveland Clinic
7:45 Valve Surgery
9:03 Content adaptation: heart valve repair
10:18 Content adaptation: coronary artery
10:30 Formal Representation for Reasoning
12:17 Cyc - 1
15:42 Simple Language, MANY terms
17:40 Senses of ‘In’
20:09 For Inference: Senses of ‘In’
21:01 Syntactic Power
24:14 OpenCyc - 1
25:44 OpenCyc - 2
26:17 OpenCyc - 3
26:33 OpenCyc - 4
26:34 OpenCyc - 5
26:35 OpenCyc - 6
26:36 OpenCyc - 7
26:37 Detailed Representations - 1
32:20 Detailed Representations - 2
32:21 Automatic Term Learning - 1
34:00 Automatic Term Learning - 2
34:34 Reasoning from Triple Store Data
36:39 inCyc - 1
37:50 inCyc - 2
38:12 inCyc - 3
38:13 inCyc - 4
38:15 inCyc - 5
38:16 inCyc - 6
38:17 inCyc - 7
38:18 inCyc - 8
38:19 Knowledge for People
38:47 What goes on a inCyc Page?
38:48 Knowledge for People
38:50 What goes on a inCyc Page?
40:28 InCyc HTML Production Rules
42:44 Use case – systems biology
43:01 Overwhelming Biological Data
46:05 The Big Picture: AI assistance - 1
48:17 The Big Picture: AI assistance - 2
48:52 Types of Reasoning, Knowledge
53:14 Cyc - 2
53:15 linked life data
54:00 Syntactic Power
55:53 Pilot experiment: GWAS-bone
57:07 Reviewing causal hypotheses
58:25 Human-readable explanations
59:22 Clearer than logic
59:32 Richly represented knowledge - 1
60:09 Richly represented knowledge - 2
60:15 Applying richer knowledge
62:05 Is the pathway justified
63:00 More detailed model
64:12 Collaborative Knowledge Creation - 1
64:27 Collaborative Knowledge Creation - 2
65:06 Collaborative Knowledge Creation - 3
65:27 Collaborative Knowledge Creation - 4
65:37 Collaborative Knowledge Creation - 5
65:41 Collaborative Knowledge Creation - 6
66:23 Collaborative Knowledge Creation - 7
66:30 Collaborative Knowledge Creation - 8
66:34 Collaborative Knowledge Creation - 9
66:35 Collaborative Knowledge Creation - 10
66:48 Collaborative Knowledge Creation - 11
66:54 Collaborative Knowledge Creation - 12
67:08 Collaborative Knowledge Creation - 13
67:17 Collaborative Knowledge Creation - 14
67:19 Collaborative Knowledge Creation - 15
67:40 Collaborative Knowledge Creation - 16
67:44 Patient Data: Metabolic Products - 1
67:47 Collaborative Knowledge Creation - 16
68:16 Patient Data: Metabolic Products - 1
68:21 Patient Data: Metabolic Products - 2
68:22 Richer Data, Richer Knowledge - 1
68:34 Richer Data, Richer Knowledge - 2
69:13 Richer Data, Richer Knowledge - 3
69:45 Scaling out and scaling up - 1
70:09 Scaling out and scaling up - 2
72:03 Scaling out and scaling up - 3
74:01 Scaling out and scaling up - 4
74:09 Scaling out and scaling up - 5
74:21 Scaling out and scaling up - 6
74:23 Scaling out and scaling up - 7
74:26 Scaling out and scaling up - 8
74:26 Scaling out and scaling up - 9
74:30 Scaling out and scaling up - 10
75:17 Scaling out and scaling up - 11
76:32 Noun Compound Parsing
79:19 Noun Phrase Parsing - 1
80:02 Noun Phrase Parsing - 2
80:31 Noun Phrase Parsing - 3
81:43 Noun Phrase Parsing - 4
82:24 Noun Phrase Parsing - 5
82:26 Taking Advantage of Paraphrases - 1
85:05 Taking Advantage of Paraphrases - 2
85:06 Taking Advantage of Paraphrases - 3
85:07 Taking Advantage of Paraphrases - 4
85:08 Taking Advantage of Paraphrases - 5
85:09 Taking Advantage of Paraphrases - 6
85:09 Cyc - 3

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Description

Human Computer Collaboration allows societies to make best use of the varied abilities of human, organizational and software agents, by allowing each to work on parts of problems and tasks that they are most suited for, and find most fulfilling. To enable true human/computer collaboration, knowledge needs to be freely communicated between the forms that each finds most useful (text, speech and images, notably for people; logic, program fragments, probabilities, databases and numeric values, notably for machines). Doing so enables new kinds of applications, that take advantage of the creativity and broad intelligence of people, and of the persistence and attentional and memory reach of computers. I will illustrate this with an application in systems biology. Free flow between these human and computer representations has not yet been achieved, but we are making progress. In this talk, I will focus on elements of this progress at Cycorp, where a partial ability to map between logical and textual representations, sometimes interactively, is beginning to significantly enhance our ability to build broad-coverage, reasoning-based applications.

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