Measuring adjective spaces

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Abstract

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 the results between the three methods are comparable, the NeRV performs best of the three, and all of them are able to preserve meaningful information for further analysis. © 2010 Springer-Verlag Berlin Heidelberg.

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Honkela, T., Lindh-Knuutila, T., & Lagus, K. (2010). Measuring adjective spaces. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6352 LNCS, pp. 351–355). https://doi.org/10.1007/978-3-642-15819-3_46

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