On-going Students Research Projects
Web-interface to identify SEO success factors
The appetite and interest in digital advertising
among small and medium enterprises is significant, but the extravagant
complexities of implementing a purposeful and benchmarked digital
advertising campaign prevent many SMEs and micro-enterprises from
engaging in strategically planned digital marketing; despite its’
relative cost effectiveness compared to traditional channels. Many SEO
success factors have been proved to be useful for improving marketing
performance. However, many companies still rely on their anecdotal
evidences or heuristics for digital marketing decision-making. This
research is focused on addressing this gap by identifying an
evidence-based SEO success roadmap for dental service providers. SMEs
that have not adopted these SEO success factors will benefit from this
research study.
Time Series Based Prediction for Isolated Power Grid Energy Consumption
By using the deep learning method, we can predict the power consumption distribution, which can help the system to schedule the HVAC running time.