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Abstract
In this chapter we describe the approach to parallel implementation of similarities in high dimensional spaces. The similarities computation have been used for textual data categorization. A test datasets we create from Wikipedia articles that with their hyper references formed a graph used in our experiments. The similarities based on Euclidean distance and Cosine measure have been used to process the data using k-means algorithm. We describe the evaluation method used of the clustering quality as its parallel implementation. Finally we discuss achieved results, point some improvements and perspectives for future development. Proposed implementation can be used as evaluation task for measuring the relevancy of simulator described in Chapter.
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- Category:
- Monographic publication
- Type:
- rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym
- Title of issue:
- W : Modeling large-scale computing systems ; concepts and models strony 149 - 160
- Language:
- English
- Publication year:
- 2013
- Bibliographic description:
- Szymański J.: Parallel Computations of Text Similarities for Categorization Task// W : Modeling large-scale computing systems ; concepts and models/ Gdańsk: Gdańsk Univesity of Technology, 2013, s.149-160
- Verified by:
- Gdańsk University of Technology
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