Back to Home

Request Correction

Use this form to request corrections to the paper metadata. Select the fields that need correction and provide the correct information.

Correction Guidelines

  1. Click the edit button next to a field to report a correction.
  2. Fill in the suggested correction value for each field you want to correct.
  3. Provide your name and email so we can contact you if needed.

Paper Information

lrec2020-ws-sltu-36

Voted-Perceptron Approach for Kazakh Morphological Disambiguation

Paper Fields

Click the edit button next to a field to report a correction.

Title

Voted-Perceptron Approach for Kazakh Morphological Disambiguation

Abstract

This paper presents an approach of voted perceptron for morphological disambiguation for the case of Kazakh language. Guided by the intuition that the feature value from the correct path of analyses must be higher than the feature value of non-correct path of analyses, we propose the voted perceptron algorithm with Viterbi decoding manner for disambiguation. The approach can use arbitrary features to learn the feature vector for a sequence of analyses, which plays a vital role for disambiguation. Experimental results show that our approach outperforms other statistical and rule-based models. Moreover, we manually annotated a new morphological disambiguation corpus for Kazakh language.


Authors

Expand an author to correct their information. Use the remove button to request author removal, or add a new author.


PDF Attachment

You may attach a PDF as a corrected version of the paper. Max file size: 10MB. Only PDF files are accepted.

Drag & drop a PDF here, or click to select

Your Information

Author Declaration *

Select at least one field to correct using the edit buttons above.