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Computing Word Senses by Semantic Mirroring and Spectral Graph Partitioning
Linköping University, Department of Mathematics, Scientific Computing.
2010 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In this thesis we use the method of Semantic Mirrors to create a graph of words that are semantically related to a seed word. Spectral graph partitioning methods are then used to partition the graph into subgraphs, and thus dividing the words into different word senses. These methods are applied to a bilingual lexicon of English and Swedish adjectives. A panel of human evaluators have looked at a few examples, and evaluated consistency within the derived senses and synonymy with the seed word.

Place, publisher, year, edition, pages
2010. , 51 p.
Keyword [en]
Cheeger inequality, Fiedler value, Fiedler vector, Graph partitioning, Normalised Laplacian, Semantic mirror, Word senses.
National Category
URN: urn:nbn:se:liu:diva-57103ISRN: LiTH-MAT-EX--2010/11--SEOAI: diva2:330160
Physics, Chemistry, Mathematics
Available from: 2010-08-10 Created: 2010-06-09 Last updated: 2011-03-22Bibliographically approved

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Scientific Computing

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