Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/476185
Title: A hybrid method of linguistic approach and statistical method for nested noun compound extraction
Authors: Hamed Hamdoon Ali Al-Balushi (P65643 )
Supervisor: Mohd. Juzaiddin Ab Aziz, Prof. Dr.
Keywords: Hybrid method
Universiti Kebangsaan Malaysia -- Dissertations
Dissertations, Academic -- Malaysia
Issue Date: 9-Jun-2014
Description: Arabic noun compound extraction has become a challenging issue in the field of NLP. Several approaches have been proposed in terms of extracting Arabic noun compounds. Some of them have used linguistic-based approach, statistical methods and the rest have used a hybrid between them. However, there is still a significant demand for improving nested Arabic noun compound extraction in terms of the accuracy. This research proposes a hybrid method of linguistic-based approach and statistical method in order to enhance the extraction of nested Arabic noun compound. The dataset has been collected from online Arabic newspaper archive from Aljazeara.net and Almotamar.net. Several pre-processing steps have been carried out on the data including transformation, normalization, stemming and POS tagging. After that, an n-gram is used to generate bi-gram, tri-gram, 4-gram, and 5-gram candidates of noun compound. Then three association measures which are NC-value, PMI and LLR have been used in order to rank the candidates. The evaluation has been performed using the n-best method with a human annotation (manual selection by expertise). NC-value has outperformed PMI and LLR in terms of extracting nested noun compounds.,Master of Information Technology
Pages: 84
Call Number: P98.A434 2014 3 tesis
Publisher: UKM, Bangi
URI: https://ptsldigital.ukm.my/jspui/handle/123456789/476185
Appears in Collections:Faculty of Information Science and Technology / Fakulti Teknologi dan Sains Maklumat

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