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This study focuses on presenting a development trend from the perspective of data-oriented evidence, especially open data and technologies, as those numbers can verify and prove current technology trends and user information requirements. According to the practical progress of Dr. What-Info I and II, this paper continues to develop Dr. What-Info III. Moreover, big data technology, the MapReduce paralleled decrement mechanism of the cloud information agent CEOntoIAS, which is supported by a Hadoop-like framework, Software R, and time series analysis are adopted to enhance the precision, reliability, and integrity of cloud information. Furthermore, the proposed system app receives a collective satisfaction score of 80% in terms of Quesenbery’s 5Es and Nielsen ratings. In addition, the verification results of the interface design show that the human-machine interface of our proposed system can meet important design preferences and provide approximately optimal balance. The top-n experiment shows that the top-5 recommendations would be better for solving the traditional tradeoff between output quality and processing time. Finally, the system effectiveness experiments indicate that the proposed system receives an overall up-to-standard function rate of 87.5%, and such recommendations provide this system with high information correctness and user satisfaction. Although there is plenty of room for improvement in experience, the feasibility of this service architecture has been proven.

A Big Data and Time Series Analysis Technology-Based Multi-Agent System for Smart Tourism