Embedded Files
Provide a scenario of a problem in your chosen industry and how data mining can solve it.
Provide a scenario of a problem in your chosen industry and how data mining can solve it.
The introduction should have the following items:
1. An industrial scenario as your problem statement. Your hypothesis on what kind of data mining solution could solve the problem and how.
2. Describe 2 stories/news on commercial application and 2 academic papers of data mining in the chosen industry. Provide the complete URL of the news and academic papers. Discuss about their differences and suggest more advancements that could have happened.
At the left side of this page create a video (you may use a slideshow as well) to give an elevator pitch about your assignment/project. At the end of the video you need to introduce your team members (please provide pictures as well). An EXAMPLE is provided for you.
As a reference on elevator pitch, see here:
https://www.mindtools.com/pages/article/elevator-pitch.htm
https://www.thebalancecareers.com/elevator-speech-examples-and-writing-tips-2061976
https://www.monster.com/career-advice/article/how-to-do-an-elevator-pitch
The following is an example on introducing about the scenario on the chosen domain (provided example below is on health). You should provide 2 examples of commercial applications and 2 examples of research papers. The example below is written in italics to differentiate between the instructions and examples. Please DO NOT forget to provide the references.
The following is an example on introducing about the scenario on the chosen domain (provided example below is on health). You should provide 2 examples of commercial applications and 2 examples of research papers. The example below is written in italics to differentiate between the instructions and examples. Please DO NOT forget to provide the references.
Example:
Risk of dengue fever exists in tropical and subtropical areas of Central America, South America, Africa, Asia, and Oceania. It is a virus-caused disease spread by the bite of the Aedes Aegypti mosquito and is more prevalent in urban areas. In Malaysia, dengue fever is the most prevalent infectious disease [1] and it has been on the rise in Malaysia over the past 40 years. For more information about dengue, visit here.
Application for dengue monitoring could provide information about the emerging outbreak. A startup company from Malaysia has won a competition through the iDengue app which could control the outbreak from reaching a severe stage.
Studying the pattern of dengue cases can help in forestalling its outbreak and functions as a warning system to alert the stakeholders (such as the residents, hospital and officers at District Health Office) to take preventive actions. For example, in [2], a study on the relationship of the factors that contribute to dengue cases was done based on Selayang and Bandar Baru Bangi. 81 weeks data is collected where three factors are focused which are aedes population size, environmental data and epidemiological record. The ovitraps are used for the first factor where the number of larvae was used to reflect Aedesmosquito population size; followed by RT-PCR screening to detect and serotype dengue virus in mosquitoes. Environmental data such as rainfall, temperature, relative humidity and air pollution index (API) were used besides epidemiological endpoint including notified cases, date of disease onset, and number and type of the interventions. The relationship is modeled using Correlation and Autoregressive Distributed Lag Model. The study showed that, notified cases were indirectly related with the environmental data but shifted one week. Notified cases were also related with next week intervention, while conventional intervention only happened 4 weeks after larvae were found, indicating ample time for dengue transmission. A high accuracy of 84.9% for Selayang and 84.1% for Bandar Baru Bangi are obtained in predicting the actual notified cases based on a significant relationship among the three factors (epidemiological, entomological and environmental).
In this study, we propose to develop a prediction model for the prediction of number of dengue cases by utilizing the rainfall and temperature data. We also investigate the
References:
[1] http://www.thesundaily.my/news/2017/08/02/dengue-fever-most-prevalent-infectious-disease-malaysia
[2] R. Ahmad, I. Suzilah, W. M. A. W. Najdah, O. Topek, I. Mustafakamal, and H. L. Lee, “Factors determining dengue outbreak in Malaysia,” PLoS One, vol. 13, no. 2, pp. 1–13, 2018 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5825112/ .
Google Sites
Report abuse