Application of Speech Recognition Interaction and Internet of Things in Data Mining

Abstract

The current data mining technology cannot attain the database of voice retrieval, and the data mining process has a high risk of interference. Therefore, the application of speech recognition interaction and Internet of Things (IoT) technology in data mining has been investigated. Using a speech recognition engine to recognize a user’s intention, a database retrieval model based on speech recognition interaction has been constructed. To enhance the security of data mining, the IoT data were classified by differential privacy clustering, and the false data features of IoT were detected efficiently. Finally, data mining was completed by combining data fusion and a Bayesian classifier. Experimental results demonstrated that the accuracy of the proposed method is over 90%, the time of data fusion is shorter, the time of data mining is shorter, the precision is higher, and the false alarm rate is lower than 5%.