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The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

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Research Article | Open Access |

Unsupervised Morphological Relatedness

Author 1: Ahmed Khorsi Author 2: Abeer Alsheddi
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 10 · Published 2016

DOI: https://doi.org/10.14569/IJACSA.2016.071047

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Abstract

Assessment of the similarities between texts has been studied for decades from different perspectives and for several purposes. One interesting perspective is the morphology. This article reports the results on a study on the assessment of the morphological relatedness between natural language words. The main idea is to adapt a formal string alignment algorithm namely Needleman-Wunsch’s to accommodate the statistical char-acteristics of the words in order to approximate how similar are the linguistic morphologies of the two words. The approach is unsupervised from end to end and the experiments show an nDCG reaching 87% and an r-precision reaching 81%.

Keywords

Arabic Language Computational Linguistics Morphological Relatedness Semitic Morphology Unsupervised Learning

How to Cite this Article

Khorsi, A., & Alsheddi, A. (2016). Unsupervised Morphological Relatedness. International Journal of Advanced Computer Science and Applications, 7(10). https://doi.org/10.14569/IJACSA.2016.071047

Khorsi, Ahmed, and Abeer Alsheddi. "Unsupervised Morphological Relatedness." International Journal of Advanced Computer Science and Applications, vol. 7, no. 10, 2016, https://doi.org/10.14569/IJACSA.2016.071047.

@article{Khorsi2016,
  title     = {Unsupervised Morphological Relatedness},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {10},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Ahmed Khorsi and Abeer Alsheddi},
  doi       = {10.14569/IJACSA.2016.071047},
  url       = {https://doi.org/10.14569/IJACSA.2016.071047}
}

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