We have abundance of schools, colleges and universities around the world. Such institutions are backbone of any developed society and are core to growth and civilization. We provide almost every kind of educational areas in science and arts, broadly speaking. Basic schooling is everybody's right in any society regardless of their poverty or skill level. However, statistics show that not every individual will go through same level of education as of others. In addition to this, some of individuals don't get to area of education; their inner talent is made for. For example, it is not uncommon for a very technical person (by birth) ends up in non-technical education path and real world jobs. Such scenarios and examples are everywhere. This results in an inefficient distribution of education and skills to right individuals. To solve this problem, I pursue researching big and unstructured data from all sources that is related to education, career and talent. In such exploration, I also focus on social networking data and mine it to analyze hidden personality features that can contribute to understand different personalities. In this research, I explore various data and analysis techniques to implement algorithms and models through lens of cognitive computing and artificial intelligence. I aim to use a very huge data set, so machine learning and training data techniques can be implemented to correlate features. I believe such analysis and mining of data, identify new educational areas, curriculum and sectors, that we must introduce to ours schools and colleges, in order to provide very customized education to a very special individuals that normally don't fit in standard educational system and fail to retain normal journey. This research is in conjunction (and part of, result of) with our other research work/initiatives in data mining, personality prediction, educational data mining and artificial intelligence, which we are pursuing and sharing with community in journals and conference at present.
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