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Saturday, 29 August 2015 QuantumML: Modelling Hidden Worlds of Information Ghislain Fourny Master‘s Thesis Presentation - March 29 th, 2007 © Department.

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Presentation on theme: "Saturday, 29 August 2015 QuantumML: Modelling Hidden Worlds of Information Ghislain Fourny Master‘s Thesis Presentation - March 29 th, 2007 © Department."— Presentation transcript:

1 Saturday, 29 August 2015 QuantumML: Modelling Hidden Worlds of Information Ghislain Fourny Master‘s Thesis Presentation - March 29 th, 2007 © Department of Computer Science | ETH Zürich

2 Saturday, 29 August 2015 Department of Computer Science 2 Why hidden worlds of information?

3 Saturday, 29 August 2015 Department of Computer Science 3 Why hidden worlds of information?

4 Saturday, 29 August 2015 Department of Computer Science 4 Why hidden worlds of information?

5 Saturday, 29 August 2015 Department of Computer Science 5 Why hidden worlds of information?  State-of-the-art search engines „merely“ look for documents containing the words you give.  No Artificial Intelligence behind.  Though: IMDB with languages.

6 Saturday, 29 August 2015 Department of Computer Science 6 Why hidden worlds of information? Haus Tier Mutter Fenster House Animal Mother Window German world English world

7 Saturday, 29 August 2015 Department of Computer Science 7 Why hidden worlds of information? Haus Tier Mutter Fenster House Animal Mother Window German world English world

8 Saturday, 29 August 2015 Department of Computer Science 8 Why hidden worlds of information? Haus Tier Mutter Fenster House Animal Mother Window German world English world The job of Artificial Intelligence Research

9 Saturday, 29 August 2015 Department of Computer Science 9 Ontologies used in AI  Assertions:  „Bordeaux“ is red wine  The vintage is the year the wine was produced in  AI can infer ontologies from other ontologies

10 Saturday, 29 August 2015 Department of Computer Science 10 Ontologies Pinot Bordeaux Mouthfeel Vintage White wine Red wine Flavour Year Oenologist world Not-an-expert world

11 Saturday, 29 August 2015 Department of Computer Science 11 Ontologies used in AI  Given a document, it is possible to make it available in other worlds  Simplify it  Translate it ...  Job of the author, or of an automated AI Engine.

12 Saturday, 29 August 2015 Department of Computer Science 12 Ontologies used in AI  Given a document, it is possible to make it available in other worlds  Simplify it  Translate it ...  Job of the author, or of an automated AI Engine. We take this for granted

13 Saturday, 29 August 2015 Department of Computer Science 13 Questions that interest Information Systems people (us)  Suppose the AI work is all done.  How to describe a document available in several worlds?  How to perform information retrieval on it?

14 Saturday, 29 August 2015 Department of Computer Science 14 Agenda  Introduction to QuantumML  Vector and Matrices Operations  Information Retrieval

15 Saturday, 29 August 2015 Department of Computer Science 15 A Document Visible in Different Worlds?  The same document is visible in three different „worlds“:  World 1: E  World 2: G  World 3: B

16 Saturday, 29 August 2015 Department of Computer Science 16 A Document Visible in Different Worlds?  Worlds as perspectives:  From the right: E  From the front: G  From the top: B

17 Saturday, 29 August 2015 Department of Computer Science 17 A Document Visible in Different Worlds?  Such an object does not exist! Are you willing to bet on this?

18 Saturday, 29 August 2015 Department of Computer Science 18 A Document Visible in Different Worlds?

19 Saturday, 29 August 2015 Department of Computer Science 19 A Document Visible in Different Worlds? Perspective 1

20 Saturday, 29 August 2015 Department of Computer Science 20 A Document Visible in Different Worlds? Perspective 2 Perspective 1

21 Saturday, 29 August 2015 Department of Computer Science 21 A Document Visible in Different Worlds? Perspective 2 Perspective 1 Perspective 3

22 Saturday, 29 August 2015 Department of Computer Science 22 A Document Visible in Different Worlds?  How can we encode such an object in the digital world?  A proposal: |world1>foo<world1| means that “foo” is visible in the world “world1” |world2>bar<world2| means that “bar” is visible in the world “world2”

23 Saturday, 29 August 2015 Department of Computer Science 23 A Document Visible in Different Worlds?  How can we encode such an object in the digital world?  A proposal: |right>E<right| |front>G<front| |top>B<top|

24 Saturday, 29 August 2015 Department of Computer Science 24 A Document Visible in Different Worlds?  How can we encode such an object in the digital world?  A proposal: |right>E<right| |front>G<front| |top>B<top|  Quantum Markup Language (QuantumML)

25 Saturday, 29 August 2015 Department of Computer Science 25 Another Example World “mouse”: Mickey likes Minnie. World “duck”: Donald likes Daisy.

26 Saturday, 29 August 2015 Department of Computer Science 26 Another Example  It could be encoded as follows: |mouse>Mickey likes Minnie<mouse| |duck>Donald likes Daisy<duck|

27 Saturday, 29 August 2015 Department of Computer Science 27 Another Example  But it is not forbidden to be clever |mouse>Mickey<mouse| |duck>Donald<duck| likes |mouse>Minnie<mouse| |duck>Daisy<duck| „likes“ appears in all of the worlds

28 Saturday, 29 August 2015 Department of Computer Science 28 Vector and Matrix Interpretation  Remember |right>E<right| |front>G<front| |top>B<top|

29 Saturday, 29 August 2015 Department of Computer Science 29 Vector and Matrix Interpretation  Remember |right>E<right| |front>G<front| |top>B<top|

30 Saturday, 29 August 2015 Department of Computer Science 30 Vector and Matrix Interpretation  Remember |right>E<right| |front>G<front| |top>B<top|

31 Saturday, 29 August 2015 Department of Computer Science 31 Vector and Matrix Interpretation  Remember |right>E<right| |front>G<front| |top>B<top|

32 Saturday, 29 August 2015 Department of Computer Science 32 Vector and Matrix Interpretation  Remember |right>E<right| |front>G<front| |top>B<top|

33 Saturday, 29 August 2015 Department of Computer Science 33 Vector and Matrix Interpretation  Remember |right>E<right| |front>G<front| |top>B<top|

34 Saturday, 29 August 2015 Department of Computer Science 34 Vector and Matrix Interpretation  Remember |right>E<right| |front>G<front| |top>B<top|

35 Saturday, 29 August 2015 Department of Computer Science 35 Vector and Matrix Interpretation  Remember |right>E<right| |front>G<front| |top>B<top|

36 Saturday, 29 August 2015 Department of Computer Science 36 Vector and Matrix Interpretation  Remember |right>E<right| |front>G<front| |top>B<top|

37 Saturday, 29 August 2015 Department of Computer Science 37 Vector and Matrix Interpretation  Remember |right>E<right| |front>G<front| |top>B<top|

38 Saturday, 29 August 2015 Department of Computer Science 38 Vector and Matrix Interpretation  Remember |right>E<right| |front>G<front| |top>B<top|

39 Saturday, 29 August 2015 Department of Computer Science 39 Vector and Matrix Interpretation  Remember |right>E<right| |front>G<front| |top>B<top| An observable (Matrix Notation) An observable (QuantumML notation)

40 Saturday, 29 August 2015 Department of Computer Science 40 Vector and Matrix Interpretation  Remember |right>E<right| |front>G<front| |top>B<top| It is diagonal: the basis is an eigenbasis. An observable (QuantumML notation)

41 Saturday, 29 August 2015 Department of Computer Science 41 Instantiation  The user lives in a world  For example, he looks from the right, or from the top, or from the front.

42 Saturday, 29 August 2015 Department of Computer Science 42 Instantiation – shift  The user is in a state  For example an eigenstate (a vector of the eigenbasis (|right>, |front>, |top>)

43 Saturday, 29 August 2015 Department of Computer Science 43 Instantiation  The user is in an eigenstate  The observable is O

44 Saturday, 29 August 2015 Department of Computer Science 44 Instantiation  The user is in an eigenstate  The observable is O  What the user sees is given by:  In quantum physics, this corresponds to the result of the measure if the system is in an eigenstate.

45 Saturday, 29 August 2015 Department of Computer Science 45 Instantiation  The user is in an eigenstate  The observable is O  What the user sees is given by:  Two formal ways to compute it:  QuantumML notation or matrix notation

46 Saturday, 29 August 2015 Department of Computer Science 46 Instantiation: Matrix notation

47 Saturday, 29 August 2015 Department of Computer Science 47 Instantiation: Matrix notation

48 Saturday, 29 August 2015 Department of Computer Science 48 Instantiation: Matrix notation

49 Saturday, 29 August 2015 Department of Computer Science 49 Instantiation: Matrix notation

50 Saturday, 29 August 2015 Department of Computer Science 50 Instantiation: Matrix notation

51 Saturday, 29 August 2015 Department of Computer Science 51 Instantiation: Matrix notation  Interpretation: The user sees “E” when he/she is in eigenstate |right>  We were able to compute it

52 Saturday, 29 August 2015 Department of Computer Science 52 Tensor Product  We can have several “reasons” to distinguish between worlds.  Right, Front, Top (3)  Red Glasses, Green Glasses, Blue Glasses (3)  Which gives 3x3=9 worlds!  QuantumML has the power to express this as well with tensor products.

53 Saturday, 29 August 2015 Department of Computer Science 53 Tensor Product  We can have several “reasons” to distinguish between worlds.  Right, Front, Top (3)  Red Glasses, Green Glasses, Blue Glasses (3)  Which gives 3x3=9 worlds!  QuantumML has the power to express this as well with tensor products. First „metadimension“

54 Saturday, 29 August 2015 Department of Computer Science 54 Tensor Product  We can have several “reasons” to distinguish between worlds.  Right, Front, Top (3)  Red Glasses, Green Glasses, Blue Glasses (3)  Which gives 3x3=9 worlds!  QuantumML has the power to express this as well with tensor products. Second „metadimension“

55 Saturday, 29 August 2015 Department of Computer Science 55 Tensor Product: yellow car example

56 Saturday, 29 August 2015 Department of Computer Science 56 Tensor Product: yellow car example |2,red>light red<2,red| |2,green>dark green<2,green| |2,blue>black<2,blue| |1,right>door<1,right| |1,front>window<1,front| |1,top>roof<1,top|

57 Saturday, 29 August 2015 Department of Computer Science 57 Tensor Product: yellow car example |2,red>light red<2,red| |2,green>dark green<2,green| |2,blue>black<2,blue| |1,right>door<1,right| |1,front>window<1,front| |1,top>roof<1,top|

58 Saturday, 29 August 2015 Department of Computer Science 58 Our toolbox  Our QuantumML toolbox includes:  An expressive language QuantumML to describe documents visible in several worlds (observables).  Calculus with observables and user states (not necessarily eigenstates).

59 Saturday, 29 August 2015 Department of Computer Science 59 Our toolbox  Our QuantumML toolbox includes:  An expressive language QuantumML to describe documents visible in several worlds (observables).  Calculus with observables and user states (not necessarily eigenstates).  Information retrieval and user state estimation to enhance scoring.

60 Saturday, 29 August 2015 Department of Computer Science 60 Information Retrieval and User State Estimation User State Raw Search Results Aggregation Enhanced Results Estimate Update Instant State Estimate Flip-flop (next cycle) Information Retrieval and Scoring User State Estimation

61 Saturday, 29 August 2015 Department of Computer Science 61 Information Retrieval and User State Estimation User State Raw Search Results Aggregation Enhanced Results Estimate Update Instant State Estimate Flip-flop (next cycle) A weighted distribution on all of the worlds modelling the worlds the user is assumed to think in.

62 Saturday, 29 August 2015 Department of Computer Science 62 Information Retrieval and User State Estimation A weighted distribution on all of the worlds modelling the worlds the user is assumed to think in.

63 Saturday, 29 August 2015 Department of Computer Science 63 Information Retrieval and User State Estimation User State Raw Search Results Aggregation Enhanced Results Estimate Update Instant State Estimate Flip-flop (next cycle) Raw Results (from indexing table)

64 Saturday, 29 August 2015 Department of Computer Science 64 Information Retrieval and User State Estimation User State Raw Search Results Aggregation Enhanced Results Estimate Update Instant State Estimate Flip-flop (next cycle) Aggregated results („put them all in a big document- view matrix“)

65 Saturday, 29 August 2015 Department of Computer Science 65 Information Retrieval and User State Estimation User State Raw Search Results Aggregation Enhanced Results Estimate Update Instant State Estimate Flip-flop (next cycle) Estimated user state is used for scoring.

66 Saturday, 29 August 2015 Department of Computer Science 66 Information Retrieval and User State Estimation User State Raw Search Results Aggregation Enhanced Results Estimate Update Instant State Estimate Flip-flop (next cycle) An instant estimate is computing depending on the worlds in which results were found.

67 Saturday, 29 August 2015 Department of Computer Science 67 Information Retrieval and User State Estimation  Assumption: If there are a lot of results in a given world, there is a high probability that the user thinks in this world. An instant estimate is computing depending on the worlds in which results were found.

68 Saturday, 29 August 2015 Department of Computer Science 68 Information Retrieval and User State Estimation User State Raw Search Results Aggregation Enhanced Results Estimate Update Instant State Estimate Flip-flop (next cycle) The instant estimate is used to update the estimate (using Kalman filtering,...)

69 Saturday, 29 August 2015 Department of Computer Science 69 Going further  Concatenation is not commutative  But interpreting documents as vector (with occurences of the words) brings commutativity  The whole formalism can be reexpressed with tensors and it works quite well.  This is already done and described in the report.

70 Saturday, 29 August 2015 Department of Computer Science 70 Conclusion  QuantumML is an expressive language to store observables describing documents visible in different worlds.  It handles „metadimensions“  Instantiation are computable.  Framework for Information Retrieval  Estimated User State used for scoring

71 Saturday, 29 August 2015 Department of Computer Science 71 Conclusion  We transformed an IR problem into a mathematical problem  Optimizations of the vector, matrix and tensor operations?

72 Saturday, 29 August 2015 Department of Computer Science 72 Thank you for your attention!  Questions?

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