Data Mining in Film Industry - Technology, Design, Implementation, Focus

This presentation discusses the use of data mining in the film industry, focusing on the technology, design, implementation, and main focus of the concept. It covers the deployment of sensors, integration of different equipment, and monitoring of patients in real-time. The main advantage of this concept is that the interaction would be in real-time without any time lagging concept attached to it. The presentation also includes references for further reading.

DATA MINING IN FLIM
INDUSTRY

Technology
The technology which is related to the concept can be directly be related
to the aspect of creating a means of interaction with the environment.
The technology can be related to the interaction of different components
and creating a means of providing
Interaction with the environment.

Design
The design in this concept can be considered to be linked directly to the
various components which interact with the hospital industry. The
interaction is directly achieved by means of sensors which are attached
to the patient.
The main advantage which is seen in this concept is that the interaction
would be in real time without time lagging concept attached to it.

Implementation
The implementation of the technology is done mainly by:
 Deployment of sensors
 Integration of different equipment which is related to the safe guard
of the patient
 Monitoring of the patient in a timely manner which would be
implemented within the concept of the technology.

Focus
The main focus of the technology is directed towards the real tracking of
the patient. The main aspect which is related to the concept is:
 Access to the data in real time
 Manipulation of the data by professionals
 Alteration process very easy.

Reference
 Larose, D. T., & Larose, C. D. (2014). Discovering knowledge in data: an introduction to
data mining. John Wiley & Sons.
 Lu, H., Setiono, R., & Liu, H. (2017). Neurorule: A connectionist approach to data
mining. arXiv preprint arXiv:1701.01358.
 Roiger, R. J. (2017). Data mining: a tutorial-based primer. CRC Press.
 Witten, I. H., Frank, E., Hall, M. A., & Pal, C. J. (2016). Data Mining: Practical machine
learning tools and techniques. Morgan Kaufmann.
 Wu, X., Zhu, X., Wu, G. Q., & Ding, W. (2014). Data mining with big data. IEEE
transactions on knowledge and data engineering, 26(1), 97-107.