Unsupervised Morphological Relatedness

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%.

Authors and Affiliations

Ahmed Khorsi, Abeer Alsheddi

Keywords

Related Articles

Thinging for Computational Thinking

This paper examines conceptual models and their application to computational thinking. Computational thinking is a fundamental skill for everybody, not just for computer scientists. It has been promoted as skills that ar...

Method for Uncertainty Evaluation of Vicarious Calibration of Spaceborne Visible to Near Infrared Radiometers

A method for uncertainty evaluation of vicarious calibration for solar reflection channels (visible to near infrared) of spaceborne radiometers is proposed. Reflectance based at sensor radiance estimation method for sola...

Automatic Classification of Academic and Vocational Guidance Questions using Multiclass Neural Network

The educational and professional orientation is an essential phase for each student to succeed in his life and his curriculum. In this context, it is very important to take into account the interests, occupations, skills...

 Identification of Critical Node for the Efficient Performance in Manet

 This paper considers a network where nodes are connected randomly and can fail at random times. The critical-node test detects nodes, whose failures are malicious behavior, disconnects or significantly degrades the...

Feature Descriptor Based on Normalized Corners and Moment Invariant for Panoramic Scene Generation

Panorama generation systems aim at creating a wide-view image by aligning and stitching a sequence of images. The technology is extensively used in many fields such as virtual reality, medical image analysis, and geologi...

Download PDF file
  • EP ID EP91026
  • DOI 10.14569/IJACSA.2016.071047
  • Views 158
  • Downloads 0

How To Cite

Ahmed Khorsi, Abeer Alsheddi (2016). Unsupervised Morphological Relatedness. International Journal of Advanced Computer Science & Applications, 7(10), 348-355. https://europub.co.uk/articles/-A-91026