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 [4]. Experiments performed on a corpus composed of Shakespeare’s writings show its linguistic analysis and categorization abilities.
Index Terms: word perception, authorship, categorization, semantic search, Elman network, linguistic analysis, personalized code, content addressable memory.
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Liou, CY., Huang, JC., Yang, WC. (2006). Semantic Addressable Encoding. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4232. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893028_21
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DOI: https://doi.org/10.1007/11893028_21
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