Qualification: 
M.Tech, BE
v_priyanka@blr.amrita.edu

Priyanka Vivek currently serves as Assistant Professor at the Department of Computer Science, Amrita School of Engineering, Bengaluru. She is currently pursuing her Ph.D. Her areas of research include Data Mining in Healthcare, Machine Learning, Text Analytics and Software Engineering.

Education

Year of Passing Degree Name of the Board/University
2015 M. Tech. in CSE Amrita School of Engineering, Bangalore
2006 B. E. in CSE Amrita School of Engineering, Bangalore

Publications

Publication Type: Conference Paper

Year of Publication Publication Type Title

2017

Conference Paper

S. Suresh Shastri, Vivek, P., Dr. Deepa Gupta, Nayar, R. C., Rao, R., and Ram, A., “Breast Cancer Diagnosis and Prognosis using Machine Learning Techniques”, in International Symposium on Intelligent Systems Technologies and Applications (ISTA'17), Manipal University, Karnataka, 2017.

2015

Conference Paper

P. Vivek, G. Radhakrishnan, Dr. Deepa Gupta, and Dr. T.S.B. Sudarshan, “Clustering of robotic environment using image data stream”, in International Conference Communication, Control and Intelligent Systems, CCIS 2015, 2015, pp. 208-213.[Abstract]


Mobile robots are being used in various applications like space shuttles, intelligent home security, military applications or other service oriented applications where human intervention is limited. A robot has to understand its environment by analyzing the data to take the appropriate actions in the given environment. Mostly the data collected from the sensors on the robots are huge and continuous, making it impossible to store the entire data in main memory and hence allowing only single scan of data. Traditional clustering algorithms like k-means cannot be used in such environment as they require multiple scan of data. This paper presents an experimental study on the implementation of Stream KM++, a data stream clustering algorithm that effectively cluster these time series robotic image data within the memory restrictions under various conditions. Promising results are obtained from the various experiments carried out. More »»

Publication Type: Book Chapter

Year of Publication Publication Type Title

2016

Book Chapter

M. Reshma, Vivek, P., Gopalapillai, R., Dr. Deepa Gupta, and Sudarshan, T. S. B., “Multi-view Robotic Time Series Data Clustering and Analysis Using Data Mining Techniques”, in Advances in Signal Processing and Intelligent Recognition Systems, Springer, 2016, pp. 521–531.[Abstract]


In present world robots are used in various spheres of life. In all these areas, knowledge of the environment is required to perform appropriate actions. The information about the environment is collected with the help of onboard sensors and image capturing device mounted on the mobile robot. As the information collected is of huge volume, data mining offers the possibility of discovering the hidden knowledge from this large amount of data. Clustering is an important aspect of data mining which will be explored in detail for grouping the scenario from multiple views. © Springer International Publishing Switzerland 2016.

More »»
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