Tiina Lindh-Knuutila

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In this article, we are studying the differences between the European Union languages using statistical and unsupervised methods. The analysis is conducted in the different levels of language: the lexical, morphological and syntactic. Our premise is that the difficulty of the translation could be perceived as differences or similarities in different levels(More)
In time series prediction, one does often not know the properties of the underlying system generating the time series. For example, is it a closed system that is generating the time series or are there any external factors influencing the system? As a result of this, you often do not know beforehand whether a time series is stationary or nonstationary, and(More)
In this article, we study the emergence of associations between words and concepts using the self-organizing map. In particular, we explore the meaning negotiations among communicating agents. The self-organizing map is used as a model of an agent’s conceptual memory. The concepts are not explicitly given but they are learned by the agent in an unsupervised(More)
In this article, we use the model adjectives using a vector space model. We further employ three different dimension reduction methods, the Principal Component Analysis (PCA), the Self-Organizing Map (SOM), and the Neighbor Retrieval Visualizer (NeRV) in the projection and visualization task, using antonym test for evaluation. The results show that while(More)
In this article, we introduce a method to make visible the differences among people regarding how they conceptualize the world. The Grounded Intersubjective Concept Analysis (GICA) method first employs a conceptual survey designed to elicit particular ways in which concepts are used among participants, aiming to exclude the level of opinions and values. The(More)
This paper reports the first results on extracting a meaningful representation for words from multilingual parallel corpora. Independent component analysis is used to extract a number of components from statistics calculated for words in contexts. Individual components are meaningful and multilingual and words are represented as a bag of concepts model. The(More)