A short introduction to Semantic Web - 2012

1. A Basic Introduction to
Semantic Web

2. Introduction

3. Hi!
My name is
Mike Darnell.
I was born in 1974
My 1st job was
modeling underwear
& Roman toys

4. My partner is
Virode Imtarnasan -
Thai, 38 years old,
married, studied law
Career: EA, Sega, IRM…
Web: Cnngo, Vertu,
Playboy…
Is your website
targeting and engaging prospects?

5. Where we do
business

6. The Fun Bit

7. What do we need in order to
have a conversation?

8. Our ability to process
language is dependent
on two elements:

9. Syntax…

10. …& Semantics

11. But what is
“Semantics”?

12. Semantics
The study of
meaning, focused
on the relation
between
signifiers, such as
words, and what
they stand for

13. What is a
“Semantic Web”?

14. Today’s web enables
computers to
communicate using a
common SYNTAX

15. The semantics needed for
UNDERSTANDING are still
handled by us HUMANS

16. But this isn’t
the plan…

17. “I dream of a
web where
computers are
capable of
analyzing ALL
the data“
Sir Tim Berners-Lee (1999)

18. On the Semantic Web data is
interpreted by machines, allowing them
to perform the work involved in finding,
combining, and acting upon
information on the Internet

19. How?

20. By moving from this

21. To this

22. Semantic Web models are
currently based either on
Explicit Meta Data or
Implicit Deductions
regarding the content on
the page

23. Explicit Meta Data

24. “Regular” HTML

25. HTML with Schema.org
microdata semantic
annotations

26. The Explicit Meta Data is the model
supported by the W3C via it’s
Resource Description Framework (RDF)
specifications:
Subject > Predicate > Object
Thailand’s capital is Bangkok

27. Implicit Deductions

28. Many sites allow
triplet-like
deductions
without requiring
formal meta data
annotations

29. Why do we
want it?

30. A machine-friendly web =
more free human time

31. A semantic web will empower us
to understand context without
resorting to “search”

32. It will empower
computers to
accomplish tasks
and answer
questions that
currently require
human involvement

33. Searching SEMANTICALLY
rather than SYNTACTICALLY
is particularly useful for:
Content in Context
Answering questions
Best product, Ideal booking, etc.

34. Content in Context

35. A Star Trek
sequel is a
serious
ENTERPRISE

36. But Which One?

37. Google isn’t
very helpful

38. Neither is
Wikipedia

39. But a little structured
data goes a long way…

40. As does
some
context

41. Services
to check out

42. Search Engines

43. Freebase is:
“An entity graph of people, places
and things, built by a community
that loves open data.”

44. Hakia

45. Sigma

46. Lexxe

47. Qwiki

48. Aggregating and
curating content

49. “Topic Pages” are popping up on
publications everywhere

50. WSJ

51. Mashable

52. NYT

53. Reader apps

54. Semantic veteran Evri is moving
from being a search engine…

55. …to a content aggregator
and interest curator

56. Flipboard acquired
Ellerdale to power it’s
relevance and interest

57. Answering questions

58. Wolfram Alpha

59. True Knowledge

60. Assistants

61. Siri

62. Evi

63. What’s next?

64. Statistical
Analysis NLP

65. “…Over the next few months,
Google will begin spitting out
more facts and direct answers
to queries at the top of the
search-results page…”
WSJ.com

66. Google’s Knowledge Graph =
200,000,000 entities
(= ~10*Freebase)

67. The “Internet of Things”
Your fridge knows you’re
about to run out of milk
Your toilet know you’re
lactose intolerant
Etc…

69. The Next Big Thing may be
enabled by new Technology

70. But its success is
dependent on its
ability to match of
our most basic needs

71. Questions?

72. Thanks!
…I’m at mi@vimi.co
Mike