Adaptive Study Design Through Semantic Association Rule Analysis

Association mining aims to find valid correlations among data attributes, and has been widely applied to many areas of data analysis. This paper presents a semantic network-based association analysis model including three spreading activation methods. It applies this model to assess the quality of a dataset, and generate semantically valid new hypotheses for adaptive study design especially useful in medical studies. The approach is evaluated on a real public health dataset, the Heartfelt study, and the experiment shows promising results. DOI: 10.4018/978-1-4666-2651-5.ch010