Intelligent Analysis of Enterprise Advertisement Push Based on Cloud Computing and Markov Chain
With the continuous improvement of communication networks, people use wireless networks more and more frequently. Whether it be in a small entertainment venue or in a large playground, wireless networks can provide people with convenient network services. People connect to wireless networks in public places to meet their Internet needs, but also receive advertisements pushed by some web pages. This is also an important way for businesses to plan and conduct advertising. In
real life, there is often a process or phenomenon of mechanism conversion between multiple states. For example, an insurance company’s policy will transition from the effective state to the claim termination state, from the effective state to the surrender
state, or from the invalid state to the effective state. This article uses continuous-time Markov chains to build a predictive model about the probability of insurance failure or surrender, which is used to calculate the probability of being in each state at any time, and proposes a method for parameter estimation. In the actual situation, the state of the insurance policy will have an uncertain event at a specific moment, so a multi-stage Markov chain model will be used to characterize this feature. That is, at a specific moment when an uncertain event occurs, a matrix of data is used to analyze the state of the object at a certain point in time and the specific circumstances regarding its movement.
Keywords: Cloud computing; Markov chain; Corporate advertising; Intelligent analysis
L. Sui, "Intelligent Analysis of Enterprise Advertisement Push Based on Cloud Computing and
Markov Chain", Engineering Intelligent Systems, vol. 29 no. 6, pp. 403-409, 2021.