This study presents a new approach for finding semantically similar words from corpora using
window based context methods. Previous studies mainly concentrate on either finding
new combination of distance-weight measurement methods or proposing new context methods.
The main difference of this new approach is that this study reprocesses the outputs of
the existing methods to update the representation of related word vectors used for measuring
semantic distance between words, to improve the results further. Moreover, this novel technique
provides a solution to the data sparseness of vectors which is a common problem in
methods which uses vector space model.
The main advantage of this new approach is that it is applicable to many of the existing word
similarity methods using the vector space model. The other and the most important advantage
of this approach is that it improves the performance of some of these existing word similarity
measuring methods.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12610759/index.pdf |
| Date | 01 July 2009 |
| Creators | Esin, Yunus Emre |
| Contributors | Alpaslan, Ferda Nur |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
Page generated in 0.0017 seconds