Abstract
This paper presents an automatic acquisition process to acquire the semantic meaning for the words. This process obtains the representation vectors for stemmed words by iteratively improving the vectors, using a trained Elman network. Experiments performed on a corpus composed of Shakespeare's writings show its linguistic analysis and categorization abilities.
Original language | English |
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Pages (from-to) | 3150-3157 |
Number of pages | 8 |
Journal | Neurocomputing |
Volume | 71 |
Issue number | 16-18 |
DOIs | |
Publication status | Published - Oct 2008 |
Externally published | Yes |
Keywords
- Authorship
- Categorization
- Compositional representation
- Content addressable memory
- Elman network
- Linguistic analysis
- Personalized code
- Polysemous word
- Semantic search
- Stylistic similarity
- Word perception