Chief Research Scientist, PhD, Docent (Adjunct Professor)
Room T-A314 in Computer Science Building,
Konemiehentie 2, Otaniemi campus area, Espoo
- Mail address:
Aalto University School of Science,
Department of Information and Computer Science,
P.O. Box 15400, FI-00076 Aalto, Finland
- +358 50 384 1578
- +358 9 470 23277
- 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. In Proceedings of IJCNN 2012, International Joint Conference on Neural Networks, pages 2875-2883, 2012.
- Mari-Sanna Paukkeri, Marja Ollikainen, and Timo Honkela. Assessing user-specific difficulty of documents. Information Processing & Management, 2012.
- Timo Honkela, Aapo Hyvärinen, and Jaakko Väyrynen. WordICA - Emergence of linguistic representations for words by independent component analysis. Natural Language Engineering, 16(3):277-308, 2010.
- Timo Honkela, Nina Janasik, Krista Lagus, Tiina Lindh-Knuutila, Mika Pantzar, and Juha Raitio. GICA: Grounded intersubjective concept analysis - a method for enhancing mutual understanding and participation. Technical Report TKK-ICS-R41, AALTO-ICS, Espoo, December 2010.
- Nina Janasik, Timo Honkela, and Henrik Bruun. Text mining in qualitative research: Application of an unsupervised learning method. Organizational Research Methods, 12(3):436-460, 2009.
- 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.
For a full list, see my publications page. See also
- ICANN 2013 conference will be held in Sofia, Bulgaria.
Computational humanities and social sciences
The phenomena within humanities and social sciences have
traditionally been too complex to be studied
with formal and/or computational methods without a clear risk of
serious reductionism or applying very restricting background
assumptions. My long-term interest is to promote research in which
the complexity of real world phenomena is respected when computational
methods are developed and applied. Methodologically the focus is
in statistical machine learning and agent-based simulation methods.
With a number of collaborators, I have published articles e.g. related to
linguistics, philosophy, sociology, psychology, economics,
cognitive studies of religion and political science.
Machine learning for multilingual and multiprofessional communication
The basic motivation of for my research in this area
stems from the need for language-independent and context-sensitive
semantics that will speed up development of
natural language processing tools and their
applications, and the need for new neurocognitive
approaches to natural language
processing. Machine learning methods make it possible, among other
things, create models of conversational language
with a large proportion of spelling mistakes,
unusual or incomplete syntactic structures,
abbreviations and creative use of language with rapid
introduction of new lexical items and expressions.
According to a commonly held view, concepts are seen independent of any
historical, contextual or subjective factors. However,
due to differences in the individual life and learning paths,
different subjects have gained different conceptual
constructions. Therefore, the language use includes subcultures as
well as individual idiosyncrasies. My research objective is to develop
theories and methods that are based on the recognition of subjectivity
of understanding the world and language.
T-61.5020 Statistical modeling of natural language,
Spring 2005, ..., Spring 2011
T-61.6090 Special course in language technology, Autumn 2005, ...., Autumn 2009
Married to Nina Honkela, two children. Hobbies: go, golf, photography.