Classification of Reliable Content on Cancer Thai Website using CancerDic+

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สุภาพร เกิดกิจ
องอาจ อุ่นอนันต์
พยุง มีสัจ


- Nowadays, there are a lot of informative websites about cancer which enables users to access data easily. However, it is difficult to determine whether these websites are reliable. The objective of this research was to develop a method which could classify the credibility of a cancer website and then determine if the information was reliable. To achieve the above goal, this research applied CancerDic+ to extract words. Technical terms referring to cancer were added to a database, and then text mining was applied to classify inputted data. The values of accuracy, precision and recall derived from the word extraction by Lexto, SWATH and CancerDic+ were then compared. The results showed that text mining for word extraction by CancerDic+ yielded the best result (Accuracy = 0.844, Precision = 0.838, Recall =0.845). In conclusion, this classification method successfully gained high accuracy and can be used in other fields effectively.

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How to Cite
เกิดกิจ ส., อุ่นอนันต์ อ., and มีสัจ พ., “Classification of Reliable Content on Cancer Thai Website using CancerDic+”, JIST, vol. 5, no. 2, pp. 34–43, Dec. 2015.
Research Article: Soft Computing (Detail in Scope of Journal)