Log in
Language:

MERAL Myanmar Education Research and Learning Portal

  • Top
  • Universities
  • Ranking
To
lat lon distance
To

Field does not validate



Index Link

Index Tree

Please input email address.

WEKO

One fine body…

WEKO

One fine body…

Item

{"_buckets": {"deposit": "3906ceb7-eb7d-499f-b4a3-83d02bcea843"}, "_deposit": {"created_by": 45, "id": "6755", "owner": "45", "owners": [45], "owners_ext": {"displayname": "", "username": ""}, "pid": {"revision_id": 0, "type": "depid", "value": "6755"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/00006755", "sets": ["user-uit"]}, "communities": ["uit"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Machine Learning Algorithms For Myanmar News Classification", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Text classification is a very important research area in machine learning. Artificial Intelligence is reshaping text classification techniques to better acquire knowledge. In spite of the growth and spread of AI in text mining research for various languages such as English, Japanese, Chinese, etc., its role with respect to Myanmar text is not well understood yet. The aim of this paper is comparative study of machine learning algorithms such as Naïve Bayes (NB), k-nearest neighbours (KNN), support vector machine (SVM) algorithms for Myanmar Language News classification. There is no comparative study of machine learning algorithms in Myanmar News. The news is classified into one of four categories (political, Business, Entertainment and Sport). Dataset is collected from 12,000 documents belongs to 4 categories. Well-known algorithms are applied on collected Myanmar language News dataset from websites. The goal of text classification is to classify documents into a certain number of pre-defined categories. News corpus is used for training and testing purpose of the classifier. Feature selection method, chi square algorithm achieves comparable performance across a number of classifiers. In this paper, the experimental results also show support vector machine is better accuracy to other classification algorithms employed in this research. Due to Myanmar Language is complex, it is more important to study and understand the nature of data before proceeding into mining."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Text Classification"}, {"interim": "Machine Learning"}, {"interim": "Feature Extraction"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2020-12-12"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Machine Learning Algorithms For Myanmar News Classification.pdf", "filesize": [{"value": "221 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "mimetype": "application/pdf", "size": 221000.0, "url": {"url": "https://meral.edu.mm/api/files/3906ceb7-eb7d-499f-b4a3-83d02bcea843/%20Machine%20Learning%20Algorithms%20For%20Myanmar%20News%20Classification.pdf"}, "version_id": "4b510265-5430-4ea3-9a76-c04d23bae65c"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_journal_title": "International Journal on Natural Language Computing (IJNLC)", "subitem_pages": "17-24", "subitem_volume": "Vol.8, No.4"}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Khin Thandar Nwet"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Journal article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2019-08-01"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "10.5121/ijnlc.2019.8402"}, "item_title": "Machine Learning Algorithms For Myanmar News Classification", "item_type_id": "21", "owner": "45", "path": ["1596102355557"], "permalink_uri": "https://meral.edu.mm/records/6755", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-12-12"}, "publish_date": "2020-12-12", "publish_status": "0", "recid": "6755", "relation": {}, "relation_version_is_last": true, "title": ["Machine Learning Algorithms For Myanmar News Classification"], "weko_shared_id": -1}
  1. University of Information Technology
  2. Faculty of Computer Science

Machine Learning Algorithms For Myanmar News Classification

https://meral.edu.mm/records/6755
https://meral.edu.mm/records/6755
fe626839-7867-43ad-9c5f-4b6255f6575e
3906ceb7-eb7d-499f-b4a3-83d02bcea843
Name / File License Actions
Machine Machine Learning Algorithms For Myanmar News Classification.pdf (221 Kb)
Publication type
Journal article
Upload type
Publication
Title
Title Machine Learning Algorithms For Myanmar News Classification
Language en
Publication date 2019-08-01
Authors
Khin Thandar Nwet
Description
Text classification is a very important research area in machine learning. Artificial Intelligence is reshaping text classification techniques to better acquire knowledge. In spite of the growth and spread of AI in text mining research for various languages such as English, Japanese, Chinese, etc., its role with respect to Myanmar text is not well understood yet. The aim of this paper is comparative study of machine learning algorithms such as Naïve Bayes (NB), k-nearest neighbours (KNN), support vector machine (SVM) algorithms for Myanmar Language News classification. There is no comparative study of machine learning algorithms in Myanmar News. The news is classified into one of four categories (political, Business, Entertainment and Sport). Dataset is collected from 12,000 documents belongs to 4 categories. Well-known algorithms are applied on collected Myanmar language News dataset from websites. The goal of text classification is to classify documents into a certain number of pre-defined categories. News corpus is used for training and testing purpose of the classifier. Feature selection method, chi square algorithm achieves comparable performance across a number of classifiers. In this paper, the experimental results also show support vector machine is better accuracy to other classification algorithms employed in this research. Due to Myanmar Language is complex, it is more important to study and understand the nature of data before proceeding into mining.
Keywords
Text Classification, Machine Learning, Feature Extraction
Identifier 10.5121/ijnlc.2019.8402
Journal articles
International Journal on Natural Language Computing (IJNLC)
17-24
Vol.8, No.4
Back
0
0
views
downloads
See details
Views Downloads

Versions

Ver.1 2020-12-12 15:10:53.907137
Show All versions

Share

Mendeley Twitter Facebook Print Addthis

Export

OAI-PMH
  • OAI-PMH DublinCore
Other Formats
  • JSON

Confirm


Back to MERAL


Back to MERAL