Enhancing Latent Semantic Analysis by Embedding Tagging Algorithm in Retrieving Malay Text Documents

Rahman, Nurazzah Abd; Soom, Afiqah Bazlla Md; Ismail, Normaly Kamal

doi:10.1007/978-3-319-56660-3_27

Cited by 5 publications

(3 citation statements)

References 11 publications

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“…Hadith classification process for content is appropriate when using BoW text representation model in TC. Hadith classification process for content is usually classifying the hadith according to the topic in the hadith books [31] [32]. Research in hadith classification that used BoW text representation can see in [6][7] [20][10][14] [1].…”

Section: Confusion Matrixmentioning

confidence: 99%

Hadith Text Classification: A Literature Review

Alias¹,

Rahman²,

Ismail³

et al. 2020

Proceedings of the Proceedings of the 2nd International Conference on Quran and Hadith Studies Information Technology and Media

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Hadith text classification is a domain specific research which requires involvement from both -science computer and hadith researcher. This paper presents literature on hadith text classification from different perspective in computer science such as classification process and issues related to it. This research therefore look into develop standard data set for hadith text classification with narrator chain part of the text as the basis. It will be the basis for future research on the classification of Malaytranslated hadith text.

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Section: Confusion Matrixmentioning

confidence: 99%

Hadith Text Classification: A Literature Review

Alias¹,

Rahman²,

Ismail³

et al. 2020

Proceedings of the Proceedings of the 2nd International Conference on Quran and Hadith Studies Information Technology and Media

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“…Because of the shortage of the structured knowledge base, it is hard to establish automatic ontology in practice. The latent semantic indexing (LSI) model supposes that the words that are close in meaning will appear in analogous fragments of text (Rahman, Soom, & Ismail, 2017). LSI yields a set of concepts related to the documents and terms.…”

Section: Introductionmentioning

confidence: 99%

Comprehending international important Ramsar wetland documents using latent semantic topic model in kernel space

Lin

Jiang

et al. 2019

Natural Resource Modeling

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The kernel‐based statistical semantic topic model is introduced for comprehending three species of internationally important Ramsar wetland documents describing the Lashi Lake wetland in the Yunnan Province, the Yancheng wetland in the Jiangsu Province, and the Zoige wetland in the Sichuan Province of China. Latent Dirichlet allocation (LDA) features are used to represent the semantic components of wetland documents. Kernel principal component analysis (KPCA) maps the topic components to the kernel space to attain the low dimensional principal components. Support vector machines (SVMs) are used to comprehend the semantic distribution of distinct wetland documents in the kernel space. The LDA+KPCA+SVM algorithm reaches 77.0% training and 75.9% test accuracy and 0.902 training and 0.840 test mean average precision scores in the application of comprehending the wetland documents, respectively. The performance of the proposed kernel‐based model is superior to the traditional models of LDA+SVM and LDA+PCA+SVM.

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“…Hadith Sahih Al Bukhari Malay from Ar-Rahman Labs features Complete Sahih Bukhari book in Malay but this application only supports keyword search [14]. Mutiara Hadis is the pioneer of the Malay Hadith Information Retrieval [15][16][17][18][19][20]. It is one of the web-based application search engines for hadith translated in Malay language.…”

mentioning

confidence: 99%

Development of mobile application for Malay translated hadith search engine

Rahman

Syamil

Rodzman

2020

IJEECS

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This paper presents the development of mobile application for Malay Translated Hadith search engine. Limitations of current Hadith web application are the design is to optimize its usage on desktop computer but not on mobile devices, which requires simple and user friendly interface. Besides that, web application also needs internet connection to use. Due to increase usage of mobile application among mobile phone users, many existing web applications have moved to mobile based applications to cater for increasing numbers of mobile users. In this study, a mobile application for Android and iOS mobile application has been developed using Flutter framework, a hybrid mobile application framework. A Malay Translated hadith search engine mobile application can easily assist those who are seeking knowledge to learn more about certain topics in hadith, a second source of Islamic knowledge. This mobile application has search and directory features for users to browse the 2028 Sahih Bukhari hadith collection. Users can enter their query using search features to find selected hadith in Malay language. Queries will be processed for searching relevant hadith and display the results to the user. Evaluation using Recall and Precision shows that on the average Recall is 73% and Precision is 33%. Functionality testing is also conducted to test against the functional requirements or specifications. Results shows all requirements are successfully tested.

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Enhancing Latent Semantic Analysis by Embedding Tagging Algorithm in Retrieving Malay Text Documents

Cited by 5 publications

References 11 publications

Hadith Text Classification: A Literature Review

Hadith Text Classification: A Literature Review

Comprehending international important Ramsar wetland documents using latent semantic topic model in kernel space

Development of mobile application for Malay translated hadith search engine

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