Authors
Norlela Samsudin, Mazidah Puteh, Abdul Razak Hamdan, Mohd Zakree Ahmad Nazri
Publication date
2013/7/3
Journal
Proceedings of the World Congress on Engineering
Volume
3
Pages
3-5
Description
Opinions about a particular product, service or person are communicated effectively through online media such as Facebook, MySpace and Twitter. Unfortunately only a few researchers had researched on the performance of opinion mining using online messages that were written in Malay Languages. Opinion mining processing that uses Natural Language Processing approach is difficult due to the high content of noisy texts in online messages. On the other hand, opinion mining that uses machine learning approach requires a good feature selection technique since the current filter typed feature selection techniques require interference from the user to select the appropriate features. This study used a feature selection technique based on artificial immune system to select the appropriated features for opinion mining. Experiments with 2000 online movie reviews illustrated that the technique has reduced 90% of the features and improved opinion mining accuracy up to 15% with k Nearest Neighbor classifier and up to 6% with Naïve Baiyes classifier.
Total citations
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Scholar articles
N Samsudin, M Puteh, AR Hamdan, MZA Nazri - Proceedings of the World Congress on Engineering, 2013