This research presents design, experiment and development of longest-match based Stemmer for Wolaita texts. The objective of this paper is to conflate the variants of Wolaita text words into its stem with better accuracy, using Longest-Match based approach. To help the researcher how to compile the possible combination of suffixes, the deep analysis of Wolaita word morphology has been made. For data preprocess and implementation, C# programming language is used. After preprocessing, 12789 unique words are reserved to experiment this research. Out of these unique words, 1200 words are randomly selected earlier and kept separate for testing purpose. Then the developed stemmer was tested using Paice’s actual error counting method. The output on that test dataset has showed 91.84% accuracy over actual manually stemmed words. The obtained result shows that the rule based longest match approach is promising for stemming Wolaita language texts.
| Published in | International Journal on Data Science and Technology (Volume 4, Issue 3) |
| DOI | 10.11648/j.ijdst.20180403.11 |
| Page(s) | 79-83 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2018. Published by Science Publishing Group |
Stemmer, Natural Language Processing, Morphology, Longest-Match
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APA Style
Girma Yohannis Bade, Hussien Seid. (2018). Development of Longest-Match Based Stemmer for Texts of Wolaita Language. International Journal on Data Science and Technology, 4(3), 79-83. https://doi.org/10.11648/j.ijdst.20180403.11
ACS Style
Girma Yohannis Bade; Hussien Seid. Development of Longest-Match Based Stemmer for Texts of Wolaita Language. Int. J. Data Sci. Technol. 2018, 4(3), 79-83. doi: 10.11648/j.ijdst.20180403.11
AMA Style
Girma Yohannis Bade, Hussien Seid. Development of Longest-Match Based Stemmer for Texts of Wolaita Language. Int J Data Sci Technol. 2018;4(3):79-83. doi: 10.11648/j.ijdst.20180403.11
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Download@article{10.11648/j.ijdst.20180403.11,
author = {Girma Yohannis Bade and Hussien Seid},
title = {Development of Longest-Match Based Stemmer for Texts of Wolaita Language},
journal = {International Journal on Data Science and Technology},
volume = {4},
number = {3},
pages = {79-83},
doi = {10.11648/j.ijdst.20180403.11},
url = {https://doi.org/10.11648/j.ijdst.20180403.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdst.20180403.11},
abstract = {This research presents design, experiment and development of longest-match based Stemmer for Wolaita texts. The objective of this paper is to conflate the variants of Wolaita text words into its stem with better accuracy, using Longest-Match based approach. To help the researcher how to compile the possible combination of suffixes, the deep analysis of Wolaita word morphology has been made. For data preprocess and implementation, C# programming language is used. After preprocessing, 12789 unique words are reserved to experiment this research. Out of these unique words, 1200 words are randomly selected earlier and kept separate for testing purpose. Then the developed stemmer was tested using Paice’s actual error counting method. The output on that test dataset has showed 91.84% accuracy over actual manually stemmed words. The obtained result shows that the rule based longest match approach is promising for stemming Wolaita language texts.},
year = {2018}
}
TY - JOUR T1 - Development of Longest-Match Based Stemmer for Texts of Wolaita Language AU - Girma Yohannis Bade AU - Hussien Seid Y1 - 2018/07/30 PY - 2018 N1 - https://doi.org/10.11648/j.ijdst.20180403.11 DO - 10.11648/j.ijdst.20180403.11 T2 - International Journal on Data Science and Technology JF - International Journal on Data Science and Technology JO - International Journal on Data Science and Technology SP - 79 EP - 83 PB - Science Publishing Group SN - 2472-2235 UR - https://doi.org/10.11648/j.ijdst.20180403.11 AB - This research presents design, experiment and development of longest-match based Stemmer for Wolaita texts. The objective of this paper is to conflate the variants of Wolaita text words into its stem with better accuracy, using Longest-Match based approach. To help the researcher how to compile the possible combination of suffixes, the deep analysis of Wolaita word morphology has been made. For data preprocess and implementation, C# programming language is used. After preprocessing, 12789 unique words are reserved to experiment this research. Out of these unique words, 1200 words are randomly selected earlier and kept separate for testing purpose. Then the developed stemmer was tested using Paice’s actual error counting method. The output on that test dataset has showed 91.84% accuracy over actual manually stemmed words. The obtained result shows that the rule based longest match approach is promising for stemming Wolaita language texts. VL - 4 IS - 3 ER -
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