| Summary: | 碩士 === 國立臺灣科技大學 === 電機工程系 === 106 === In this age of technological improvement, communication methods are evolving constantly (e.g. instant messaging, social media and social messaging, etc.) and are widely used in our everyday lives. ”E-mail marketing” has long been an important business strategy. Businesses can provide customers with “discount offers” and share information through e-mails, so as to increase brand awareness and loyalty and sustain the business-customer relationship.
E-newsletter platforms can send as many e-mails per hour, and perhaps even have a high rate of successfully sent emails. However, if the receiving end never opens the mail, all expected benefits and calculations that follows would be lost.
By categorizing the habits of newsletter receivers when opening e-newsletters with artificial intelligence, this study will analyze the data on sending time and history of e-mails opened as provided by NewsLeopard as basis. The study will pre-process such data and categorize according to the opening time of e-mails, thereby building a categorization model with kNN. Confusion matrix will be used to evaluate the efficiency of the categorization model by comparing the model with different K-values.
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