Service Recommendation based on DIKW Pyramid
Jiamin Lv, Lei Yu, Yucong Duan · 2021
In the initial establishment of wisdom, data, information, knowledge and wisdom are a progressive relationship. When we test whether the current wisdom system is fully developed, our judgment is to verify whether the knowledge, information and data generated by the wisdom system are correct. However, the growth process of the wisdom system is not smooth sailing. It will generate wrong knowledge, information and data, and these mistakes can also be used as the raw materials for the growth of the wisdom system, that is, a more perfect wisdom system can be formed through reflection. By analyzing the process of Service Recommendation based on deep learning, we found that a Service Recommendation model based on the data, information, knowledge and wisdom has excellent performance in accuracy, reliability and other aspects. We proposed a Service Recommendation model based on DIKW Pyramid. By comparing the recommendation by the model with the service that is users' real like, the model reflects on the differences between the recommendation results and the real results, making the recommendation results closer to the real, so as to improve the accuracy of Service recommendation.