Association Rules Extraction Method for Semantic Query Processing Over Medical Big Data

Abstract

With the rapid development of online medical platform, data mining algorithms can effectively deal with an amount of online medical data and solve the complex semantic relationships among these data. However, traditional data mining algorithms may directly remove some professional terms as interference words, because professional medical terms account for a small proportion of online medical data. Therefore, we proposed TRSC algorithm to extract keywords and semantic relationships among online medical data, which support to add these words to keywords libraries based on their semantic weight. Furthermore, it can provide a complete keyword library for semantic relation extraction. Experiments show that TRSC algorithm can effectively recognize the low-frequency keywords and extend medical keywords library, it accurately mined the semantic relationships.