Timo Honkela: Self-Organizing Map as a Means for Gaining Perspectives

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Presentation on 23rd of May, 2014, in Metalithicum # 5, Computation as literacy: Self Organizing Maps, organized by ETH CAAD in Einsiedeln, Switzerland.

Program:

Thursday 22nd of May 2014

13:30-14:30 INTRODUCTION – CODING AND ARCHITECTURE
Prof. Dr. Ludger Hovestadt
Chair for Computer Aided Architectural Design, CAAD, ITA, ETH Zurich
14:30-16:00 Discussion
17:30-18:30 WARM UP TWO – PROFILING KEY CONCEPTS IN CONTINUOUS GEOMETRY
Prof. Sha Xin Wei
Director School of Arts, Media and Engineering, Herberger Institute
for Design and the Arts, Arizona State University, Founding Director
Topological Media Lab, Concordia University, Montreal.
18:30-19:00 Discussion

Friday 23rd of May 2014

08:00-09:00 WARM UP – PROFILING KEY CONCEPTS IN CATEGORY
THEORY
Prof. Michael Epperson
Center for Philosophy and the natural Science, College of Natural
Sciences and Mathematics, California State University, Sacramento, USA
10:00-10.30 Discussion
10:30-11:30 SELF-ORGANIZING MAP AS A MEANS FOR GAINING PERSPECTIVES
Prof. Dr. Timo Honkela
Department of Modern Language, University of Helsinki and
National Library of Finland
11:30-12:30 Discussion
13:00-14:00 Prof. Barbara Hammer
CITEC centre of excellence, Bielefeld University, Bielefeld, Germany
14:00-15:00 Discussion
15:30-16:30 THE PRACTICAL PROBLEM OF CALIBRATING TOPOLOGICAL
DYNAMICS AGAINST SOCIO-CULTURAL & HISTORICAL PROCESSES
Prof. Dr. Sha Xin Wei
Director School of Arts, Media and Engineering, Herberger Institute
for Design and the Arts, Arizona State University, Founding Director
Topological Media Lab, Concordia University, Montreal
16:30-17:30 Discussion
18:00-19:00 Dr. Elias Zafiris
Department of Mathematics at the University of Athens
19:00-20:00 Discussion

Saturday 24th of May 2014

9:00-10:00 Dr. André Skupin
Department of Geography San Diego State University,
http://geography.sdsu.edu/People/Pages/skupin/
10:00-11:00 Discussion
11:30-12:30 Vahid Moosavi
PhD Candidate at the Chair for Computer Aided Architectural Design,
CAAD, ITA, ETH Zurich, www.caad.arch.ethz.ch, Researcher at Future
Cities Laboratory, Singapore-ETH Centre
12:30-13:30 Discussion
14:30-15:30 THE ONTOLOGY AND EPISTEMOLOGY OF INTERNAL RELATIONS:
BRIDGING THE PHYSICAL AND CONCEPTUAL IN QUANTUM
MECHANICS AND QUANTUM INFORMATION
Prof. Dr. Michael Epperson
Center for Philosophy and the natural Science, College of Natural
Sciences and Mathematics, California State University, Sacramento, USA
15:30-16:30 Discussion
17:00-18:00 Dr. phil. Vera Bühlmann
laboratory for applied virtuality, Chair for Computer Aided
Architectural Design, CAAD, ITA, ETH Zurich
18:00-19:00 Discussion

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Timo Honkela: Self-Organizing Map as a Means for Gaining Perspectives

  1. 1. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Einsiedeln        23rd of May                    2014 Self-Organizing Map as a Means for Gaining Perspectives Timo Honkela
  2. 2. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Timo Honkela 23 May 2014 Self-Organizing Map as a Means for Gaining Perspectives timo.honkela@helsinki.fi Metalithicum # 5 Computation as literacy: Self Organizing Maps
  3. 3. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Part I: The Self-Organizing Map
  4. 4. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Teuvo Kohonen before the SOM ● School time interest in mathematics, physics, chemistry, psychology, radio technology, etc. ● Studies at Helsinki University of Technology in theoretical physics, PhD in 1962, Professor 1963- ● First designer of a computer in Finland (REFLAC), mid-1960s, keen interest on analog computers ● Visiting professor, University of Washington 1968-69 ● Research professor (funded by Academy of Finland), 1975- ● Book “Associative Memory: A Systems-Theoretical Approach”, 1978 Anderson, James A., and Edward Rosenfeld, eds. Talking nets: An oral history of neural networks. MiT Press, 2000.
  5. 5. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Kohonen, Teuvo (1982). "Self-Organized Formation of Topologically Correct Feature Maps". Biological Cybernetics 43 (1): 59–69. Kohonen, T. (1981). Self-organized formation of generalized topological maps of observations in a physical system. Report TKK-F-A450, Helsinki University of Technology, Espoo, Finland. First SOM publications
  6. 6. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Google:
  7. 7. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 SOMintroduction (Honkela 1997)
  8. 8. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Milos Manic “Poverty map” Kaski & Kohonen “Pockets Full of Memories” Legrady, Honkela et al. André Skupin “Map of Mozart” Rauber, Lidy &Mayer “WEBSOM” Honkela, Kaski, Kohonen & Lagus
  9. 9. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Variants of the SOM ● Input ● Network structure ● Learning rule – Information-theoretical – Probabilistic ● Recurrent and recursive versions ● Operator maps for dynamic phenomena ● Output presentation and postprocessing (clustering, coloring, etc.) ● Etc.
  10. 10. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Views into the SOM ● Vector quantization ● Dimensionality reduction (visualization) ● (Clustering) ● Cortical modeling ● Conceptualization (“semantification”) ● Cognitive function modeling ● Antidote against categorical thinking ● ...
  11. 11. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Different kinds of input Somervuo & Kohonen (1999): Self-organizing maps and learning vector quantization for feature sequences. Neural Processing Letters.
  12. 12. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Different kinds of map structures ● Fixed topology (rectangular, hexagonal) ● Fixed unusual topology (e.g. portrait of Mozart) ● Different dimensionalities (1-, 2-, 3-,..., mixed) ● Growing neural gas ● Hierarchical maps ● Etc. etc.
  13. 13. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Some other Kohonen algorithms ● Correlation matrix memories (1972) ● Median strings (1985) ● Learning Vector Quantization (1986) ● Dynamically Expanding Context (1986) ● Self-learning musical grammar (1989) ● Adaptive Subspace SOM (1996) ● Symbol string SOM (1998) ● Evolutionary SOM (1999) ● Self-organizing neural projections (2006) Years are partly approximate
  14. 14. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Part II: Perspectives to language, cognition and human knowing
  15. 15. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Classical example: Learning meaning from context: Maps of words in Grimm fairy tales Honkela, Pulkki & Kohonen 1995 Automated learning of word relations using self-organizing map on text context data
  16. 16. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Map of Finnish Science Chemistry Physics and engineering Biosciences Medicine Culture and society A fully automated process from terminology extraction (Likey) to semantic space construction (SOM) without any manually constructed resources.
  17. 17. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 You can measure things that were not measurable before
  18. 18. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 A. Measuring meaning
  19. 19. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Challenges: “Language is BIG” “Human INTERPRETATION is inherently involved” Texts as input instead of measurements
  20. 20. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Example: Complexity of Finnish at the level of word forms Kimmo Koskenniemi (2013): Johdatus kieliteknologiaan, sen merkitykseen ja sovelluksiin (Introduction to language technology, its significance and applications) https://helda.helsinki.fi/bitstream/handle/10138/38503/kt-johd.pdf?sequence=1
  21. 21. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 > 6000 languages, many more dialects Billions of people blogs.state.gov en.wikipedia.org A large number of different cultures en.wikipedia.org A vast number of ways to relate language, concepts and the world to each other
  22. 22. Simulating processes of language emergence and communication 22 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Language as a system ● Considering natural language as a signal and dynamic system at cognitive and social levels (also in its written form) rather than a symbolic and logical system ● Importance of embodiment (cf. e.g. Harnad) and embeddedness (cf. e.g. Edelman) ● Learning and pattern recognition processes are essential (as opposed to the theories presented e.g. by Chomsky, Fodor, Pinker); much of the learning is bound to be unsupervised
  23. 23. Simulating processes of language emergence and communication 23 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Predicate logic is not about meaning ● Formalisms like first-order predicate logic have widely been used as a basis for theories of meaning; consider also contemporary efforts such as Semantic Web ● These formalisms provide only limited means for creating in-depth theories of how language is understood ● Traditional logic provides means e.g. for modeling quantification, connectives, analytical truths and conceptual hierarchies ● However, many semantic phenomena are matters of degree. Various proposals that apply Bayesian probability theory or fuzzy sets deal with this.
  24. 24. Simulating processes of language emergence and communication 24 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Traditional AI & logic viewpoint Agents Language Model of the world World = = =
  25. 25. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Pattern recognition ● Even these methodological extensions do not suffice if the pattern recognition processes are not taken into account ● The world is not straightforwardly experienced as discrete objects and events but there are complex underlying cognitive processes involved
  26. 26. Simulating processes of language emergence and communication 26 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Agents Language World Model of the world Emergentist viewpoint (importance of pattern recognition and learning)
  27. 27. Simulating processes of language emergence and communication 27 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 General communication system and measuring information (Shannon & Weaver) INFORMATION SOURCE TRANSMITTER RECEIVER DESTINATION MESSAGE MESSAGE NOISE SOURCE SIGNAL RECEIVED SIGNAL H = - Σ pi log piNoisy channel model
  28. 28. Simulating processes of language emergence and communication 28 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Weaver on Shannon ● “Relative to the broad subject of communication, there seem to be problems at three levels. [...] – LEVEL A. How accurately can the symbols of communication be transmitted? (The technical problem) – LEVEL B. How precisely do the transmitted symbols convey the desired meaning? (The semantic problem) – LEVEL C. How effectively does the received meaning affect conduct in the desired way? (The effectiveness problem)” ● “The semantic problems are concerned with the identity, or satisfactorily close approximation, in the interpretation of meaning by the receiver, as compared with the intended meaning of the sender.” (1949, p. 4)
  29. 29. Simulating processes of language emergence and communication 29 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Distributional hypothesis ● Two words are semantically similar to the extent that their contextual representations are similar (Miller & Charles 1991) ● The meaning of words is in their use (Wittgenstein)
  30. 30. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Context is concretely relevant in physics
  31. 31. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Meaning is contextual red wine red skin red shirt Gärdenfors: Conceptual Spaces Hardin: Color for Philosophers
  32. 32. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Meaning is contextual SNOW - WHITE? WHITE
  33. 33. Simulating processes of language emergence and communication 33 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Complex challenge: different contexts and cultures “Shall I compare thee to a summer's day?” ? ?
  34. 34. Simulating processes of language emergence and communication 34 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Modeling distributional similarity: word space models ● Word space models represent meaning as points or areas in a high dimensional vector space – Self-Organizing Semantic Maps (Ritter and Kohonen 1989) – LSA (Landauer & Dumais 1997) – HAL (Lund & Burgess 1996) – Conceptual spaces (Gärdenfors 2000) – Word ICA (Honkela, Hyvärinen & Väyrynen 2004) – etc. etc.
  35. 35. Simulating processes of language emergence and communication 35 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Language as dimensionality reduction? ICA of word contexts; nonlinearity through thresholding Comparison with SVD/LSA Effect of sparseness and meaningful emergent components Data: TOEFL tests (Väyrynen, Lindqvist, Honkela 2007)
  36. 36. Simulating processes of language emergence and communication 36 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 ICA SVD precision active dimensions
  37. 37. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Point of view from cognitive linguistics ● The meaning of linguistic symbols in the mind of the language users derives from the users' sensory perceptions, their actions with the world and with each other. ● For example: the meaning of the word 'walk' involves – what walking looks like – what it feels like to walk and after having walked – how the world looks when walking (e.g. objects approach at a certain speed, etc.). – ...
  38. 38. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Abstract vs concrete grounding Ronald Langacker
  39. 39. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Motion capture AnimationImage analysis Video analysis Robotics Machine learning Language learning Socio-cognitive modeling Symbol grounding Jorma Laaksonen Tapio Takala Klaus Förger Harri Valpola Oskar Kohonen Reinforcement learning Paul Wagner Markus Koskela Xi Chen Learning relations Kinect OptiTrack Timo Honkela
  40. 40. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 goo.gl / UZnvH
  41. 41. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Förger & Honkela, 2013 WALKING RUNNINGRUNNING Consider how different languages divide the conceptual space in different ways (cf. e.g. Melissa Bowerman et al.)
  42. 42. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 B. Measuring (inter)subjectivity
  43. 43. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 “Einsiedeln Abbey is a Benedictine monastery in the town of Einsiedeln in the Canton of Schwyz, Switzerland. The abbey is dedicated to Our Lady of the Hermits, the title being derived from the circumstances of its foundation, for the first inhabitant of the region was Saint Meinrad, a hermit. It is a territorial abbey and, therefore, not part of a diocese, subject to a bishop. It has been a major resting point on the Way of St. James for centuries.” (Wikipedia) Objective facts? Other points of view?
  44. 44. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014
  45. 45. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014
  46. 46. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Non-linear projections next to Hotel Drei Könige
  47. 47. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Meaning is subjective
  48. 48. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Meaning is subjective ● Good ● Fair ● Useful ● Scientific ● Democratic ● Sustainable ● etc. A proper theory of meaning has to take this into account
  49. 49. Simulating processes of language emergence and communication 49 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Experiential grounding of human knowledge    Human understanding of the world and of  the relationship between language use  and perception and action within the  world is based on a long active and  interactive learning process for which the  genotype gives a certain basis but which  is mainly determined by the individual  interaction with the world including other  human beings and the social and cultural  context
  50. 50. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Concept Formation and Communication - General Theory Timo Honkela, Ville Könönen, Tiina Lindh-Knuutila, and Mari-Sanna Paukkeri. Simulating processes of concept formation and communication. Journal of Economic Methodology, 15(3):245–259, 2008.  λ : Ci × Cj   → R, i ≠ j A distance between  two points in the  concept spaces of  different agents S: symbol space, The vocabulary of an agent that consists of  discrete symbols : sξ i   S∈ i → C An individual  mapping function  from symbols to  concepts φi: Si   D→ An individual  mapping from agent  i's vocabulary to the  signal space D and an inverse mapping φ­ 1  i from the signal  space to the symbol  space Ci: N­dimensional  metric concept  space  Observing f1 and after symbol  selection process, agent 1  communicates a symbol s* to agent 2 as signal d.  When agent  2 observes d, it maps it  to some s2   S∈ 2  by using the function φ ­1 1.    Then it maps the symbol to some  point in its concept space by using  ξ2.  If this point is close to its  observation f2 in the sense of λ, the  communication process has  succeeded.
  51. 51. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 GICA: Grounded Intersubjective Concept Analysis
  52. 52. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Timo Honkela, Juha Raitio, Krista Lagus, Ilari T. Nieminen, Nina Honkela, and Mika Pantzar. Subjects on objects in contexts: Using GICA method to quantify epistemological subjectivity. Proceedings of IJCNN 2012, International Joint Conference on Neural Networks, pp. 2875- 2883, 2012. Publication:
  53. 53. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Case: State of the Union Addresses ● Text mining is used in populating a Subject-Object-Context tensor ● This took place by calculating the frequencies on how often a subject uses an object word in the context of a context word – Context window of 30 words
  54. 54. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Analysis of the word 'health'
  55. 55. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 This is why unsupervised learning is better in most cases in comparison with supervised learning Human-made categories cannot simply be taken as a ground truth There are even a large number of well grounded category systems, none of which has an objective status Kuhn Local … global
  56. 56. Simulating processes of language emergence and communication 56 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Relevance? ● A large proportion of modern human activity in its different forms (science, industry, society, culture, etc.) is based on the use of language ● There are at least 6000 languages in the world and many more dialects ● Each language has the order of 105 to 1010 different word forms ● Each word is understood differently by each speaker of that language at least to some degree
  57. 57. Simulating processes of language emergence and communication 57 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Relevance, cont'd ● The formal basis of in practice all information systems does not take this basic phenomenon into account ● The assumption of shared meanings is simply not adequate ● Socio-cognitive modeling is needed
  58. 58. Simulating processes of language emergence and communication 58 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Language use and theory formation as social phenomena data collection and generalization theories language use regularity, variation regularity, variation producing/ creating learning/ observing producing/ creating producing/ creating description and harmonization
  59. 59. Simulating processes of language emergence and communication 59 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Emergence of a coherent lexicon in a community of interacting SOM-based agents (Lindh-Knuutila, Lagus & Honkela, SAB'06) Related to e.g. Steels and Vogt on language games
  60. 60. Simulating processes of language emergence and communication 60 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Survival and reinforcement learning in conceptual system evolution (Honkela & Winter 2003)
  61. 61. Simulating processes of language emergence and communication 61 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Practical consequences ● The traditional notion of uncertainty in decision making does not cover the uncertainties caused by differences in conceptual systems of individual agents within a community ●  In many transactions, including symbolic/linguistic communication, the differences in the underlying conceptual systems play an important role ●  Serious efforts have been made to harmonize or to standardize the classification systems or ontologies used by agents ●  Even if standardization is conducted, there can not be any true guarantee that all participating agents would share the meaning of all the expressions used in the transactions in various contexts
  62. 62. Simulating processes of language emergence and communication 62 Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Quantifying the effect of “semantic noise” ● Sintonen, Raitio & Honkela: “Quantifying the effect of meaning variation in survey analysis”, forthcoming in ICANN 2014
  63. 63. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Part III: Closing remarks on digital humanities
  64. 64. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Digital humanities ● Research within humanities with the help of computers – Digital resources – Computational models ● Basic motivation – One can already fly to moon and build sophisticated factory products – The most important open questions in the world are related to humanities and social sciences
  65. 65. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Digital Computational Humanities Content storage and transfer Content analysis
  66. 66. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Societal and Cultural Text Mining
  67. 67. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Honkela, Korhonen, Lagus & Saarinen: Five-dimensional sentiment analysis of corpora, documents and words, forthcoming in WSOM 2014
  68. 68. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Project ఠ (ttha,Telugu) Science Society Culture
  69. 69. Timo Honkela in Metalithicum #5: Self-Organizing Map as a Means for Gaining Perspectives, Einsiedeln, 23rd of May, 2014 Thank you for your attention! Danke schön! Kiitos! Tack! Merci! 謝謝! Σας ευχαριστούμε! ¡Gracias!

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