Benchmarking Mi-POS: Malay Part-of-Speech Tagger

Xian, Benjamin Chu Min; Lubani, Mohamed; Ping, Liew Kwei; Bouzekri, Khalil; Mahmud, Rohana; Lukose, Dickson

doi:10.18178/ijke.2016.2.3.064

Cited by 8 publications

(5 citation statements)

References 9 publications

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“…However, their approach resulted in low accuracy due to incorrect mapping in language structure. The current work by Xian et al (2016) performed a benchmarking experiment on previous Malay POS approaches. Their Mi-POS used machine learning probabilistic methods for the POS tagging by referring to the training corpora.…”

Section: Malay Natural Language Processingmentioning

confidence: 99%

“…The Accuracy Results of the Mi-POS Technique Against the Existing Methods Using Two Different Testing Malay Corpora (news and nonnews) (Xian et al, 2016).…”

Section: Figurementioning

confidence: 99%

“…Furthermore, such tools are not available for public access. Several previous research in Malay POS tagger used the formal language corpus of news and non-news data (Alfred et al, 2013;Mohamed et al, 2011;Xian et al, 2016). In contrast, recent works by Ariffin and Tiun (2018) have shifted to social media texts, where the authors highlighted the issue of informal language used in Tweet texts and the need for a large training of Malay corpus to be set up.…”

Section: Introductionmentioning

confidence: 99%

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A Syntactic-Based Sentence Validation Technique for Malay Text Summarizer

Alias

Sainin

Mohammad

2021

Journal of Information and Communication Technology

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In the Automatic Text Summarization domain, a Sentence Compression (SC) technique is applied to the summary sentence to remove unnecessary words or phrases. The purpose of SC is to preserve the important information in the sentence and to remove the unnecessary ones without sacrificing the sentence's grammar. The existing development of Malay Natural Language Processing (NLP) tools is still under study with limited open access. The issue is the lack of a benchmark dataset in the Malay language to evaluate the quality of the summaries and to validate the compressed sentence produced by the summarizer model. Hence, our paper outlines a Syntactic-based Sentence Validation technique for Malay sentences by referring to the Malay Grammar Pattern. In this work, we propose a new derivation set of Syntactic Rules based on the Malay main Word Class to validate a Malay sentence that undergoes the SC procedure. We experimented using the Malay dataset of 100 new articles covering the Natural Disaster and Events domain to find the optimal compression rate and its effect on the summary content. An automatic evaluation using ROUGE (Recall-Oriented Understudy for Gisting Evaluation) produced a result with an average F-measure of 0.5826 and an average Recall value of 0.5925 with an optimum compression rate of 0.5 Confidence Conf value. Furthermore, a manual summary evaluation by a group of Malay experts on the grammaticality of the compressed summary sentence produced a good result of 4.11 and a readability score of 4.12 out of 5. This depicts the reliability of the proposed technique to validate the Malay sentence with promising summary content and readability results.

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Section: Malay Natural Language Processingmentioning

confidence: 99%

“…The Accuracy Results of the Mi-POS Technique Against the Existing Methods Using Two Different Testing Malay Corpora (news and nonnews) (Xian et al, 2016).…”

Section: Figurementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Syntactic-Based Sentence Validation Technique for Malay Text Summarizer

Alias

Sainin

Mohammad

2021

Journal of Information and Communication Technology

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“…Once each token is tagged, compound phrase that are exists in the sentence will be identified. In this study, POS tagging are based on those Malay POS tagger (Mi-POS) (Xian et. Al., 2016).…”

Section: Pos Taggingmentioning

confidence: 99%

Sentence Similarity Measurement Based Onthematic Role and Semantic Networktechniques

Hamza¹,

Aziz²,

Omar³

2019

IJSECS

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Automated Short Essay Assessment is a subjective assessment that emphasizes important contents more than writing style. Word Order Technique and Syntactic-Semantic Knowledge Technique have been used in previous researches. However, it cannot differentiate sentence pair that is not similar semantically and only proven to produce excellent result on short sentence. Thematic Role annotation for every significant argument seems able to provide information regarding the relations between the word. Wordnet Semantics Network calculates semantic similarities of two synsets (token) by taking into account the depth of semantic relations. This study is conducted on Compiler course set in Malay that comprise of passive, simple, negative, mixed and complex questions. To prove the effectiveness of the techniques, the test result that apply Grammar Pola Technique was used as a benchmark because the study uses the same data set. The average of f-measure test accuracy rate is 93.53% when using Thematic Role and Semantic Network Techniques compared to 82.36% accuracy rate when using Pola Grammar Technique. The result of Thematic Role can be used on research involving Malay linguistic to test sentence structure matching that has verb by considering types of sentence.

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“…The reason behind unique name is because of the annotation process. This method does not require heavy process of annotating the dataset for training like other method as it annotates dataset using a Besides that, a research completed by [7]for Malay POS tagger called Mi-POS revealed to have higher accuracy at 95.16%. Mi-POS is a statistical POS tagger approaches that use a large dataset.…”

Section: Named Entity Recognitionmentioning

confidence: 99%

Comparative study on corpus development for Malay investment fraud detection in website

Din

Hashim

Siraj

2018

J. Fundam and Appl Sci.

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In the online world, fraudsterscan monetary gain. Corpus development research can be use identify keywords used by fraudsters online to prevent the crime. The aim of this research is to develop a corpus for Malay investment fraud so that it can be used in detection and classification of investment fraud in Malay website and compare the most suitable technique. tagger (POS) and Named Entity Recognition (NER) tagger are selected. Proposed methodology that are used in this research is corpus development, training and development of dataset using Naïve Bayes and performance evaluation. The dataset used in this research is online news archive and discussion forums. This research able to help the law enforcements agencies in collecting and notifying the keyword used by fraudsters so that they can take any legal actions. scaneasily manipulate people to gain something and usually for monetary gain. Corpus development research can be use identify keywords used by fraudsters online to prevent the crime. The aim of this research is to develop a corpus for Malay t can be used in detection and classification of investment fraud in Malay website and compare the most suitable technique. In this research, Part tagger (POS) and Named Entity Recognition (NER) tagger are selected. Proposed used in this research is corpus development, training and development of dataset using Naïve Bayes and performance evaluation. The dataset used in this research is online news archive and discussion forums. This research able to help the law enforcements gencies in collecting and notifying the keyword used by fraudsters so that they can take any corpus development; information extraction; part-of-speech; named entity mail: mazura@utm.my http://dx.doi.org/10.4314/jfas.v9i6s.62 Journal of Fundamental and Applied Sciences http://www.jfas.info Creative Commons Attribution-NonCommercial 4.0 Research Associations category. ON CORPUS DEVELOPMENT FOR MALAY INVESTMENT FRAUD DETECTION IN WEBSITE aculty of Computing, Universiti Malaysia manipulate people to gain something and usually for monetary gain. Corpus development research can be use identify keywords used by fraudsters online to prevent the crime. The aim of this research is to develop a corpus for Malay t can be used in detection and classification of investment fraud in this research, Part-of-Speech tagger (POS) and Named Entity Recognition (NER) tagger are selected. Proposed used in this research is corpus development, training and development of dataset using Naïve Bayes and performance evaluation. The dataset used in this research is online news archive and discussion forums. This research able to help the law enforcements gencies in collecting and notifying the keyword used by fraudsters so that they can take any speech; named entity Research Article Special Issue N. Hashim et al.

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Benchmarking Mi-POS: Malay Part-of-Speech Tagger

Abstract: Index Terms-Benchmarking, Malay language, natural language processing, part-of-speech tagging.

Cited by 8 publications

References 9 publications

A Syntactic-Based Sentence Validation Technique for Malay Text Summarizer

A Syntactic-Based Sentence Validation Technique for Malay Text Summarizer

Sentence Similarity Measurement Based Onthematic Role and Semantic Networktechniques

Comparative study on corpus development for Malay investment fraud detection in website

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