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Tourism is one of the most significant industries all across the globe. Information technology plays an indispensable role in promoting the industry. We utilized a web crawler to obtain online tourists' demographics and comments. This study adopts a new perspective in analyzing tourists' profiles where both quantitative (data mining) and qualitative analysis methods were performed on the data collected...
Currently data mining techniques and health/medical informatics are still new. Data mining researchers start paying more attention on these matters. Association Rule is one of important methods in data mining. By discovering data association, new useful information can be obtained. In this paper, a researcher has presented a basic method of discovering an association of diabetes mellitus with complication...
Owing to the limitation of traditional software aging trend prediction method that based on time and based on measurement in dealing with sudden large scale concurrent questions, this paper proposes a new software aging trend prediction method which is based on user intention. This method predicts the trend of software aging according to the quantity of user requests for each components during the...
Conventional Association Rule Mining (ARM) algorithms usually deal with datasets with binary values, and expect any numerical values to be converted to binary ones using sharp partitions, like Age = 25 to 60. In order to mitigate this constraint, Fuzzy logic is used to convert quantitative values of attributes to binary ones, so as to eliminate any loss of information arising due to sharp partitioning,...
Microarray technology has created a revolution in the field of biological research. Association rules can not only group the similarly expressed genes but also discern relationships among genes. However, the efficiency of traditional method to generate association rules is not very well. We develop a novel algorithm, SAW, to generate strong association rules by combining the paired rules, which can...
In this paper we propose a new CAD (Computer Aided Diagnosis) system to classify patients with Alzheimer disease. Five textural features proposed by Harlick are extracted from the MRI scans which characterize the disease. An enhanced CBA algorithm is used to classify the images as Normal or Abnormal based on the rule set generated during the training phase. The experiments were conducted on OASIS...
DT-miner, a system that integrates association rules in the exploration framework of dynamic taxonomies,is presented. Dynamic taxonomies are a general model for the user-centric systematic and guided exploration of complex information bases. The goal of DT-miner is two-fold: from the one side, it provides a highly interactive, user-centered environment for the exploration of significant association...
This paper proposes a method to detect abnormal event in solitary elder's daily life by mining the related data gained by sensors. It is analyzed that the relationship between elder's activity time distribution and the activity, and then the association rules of elder's actions is obtained. It can help to detection abnormal activity and provide timely and appropriate services to the solitary elder.
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