Training in Big Text Data (TRIBE)

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We propose an industrial stream, advanced, collaborative graduate Training program in Big Text Data (TRIBE). On the one hand, Big Text represents additional challenges with respect to Big Data, as the information is unstructured and presented in (often simplified or incorrect) natural language. On the other hand, Big Text is ubiquitous in business, science, and everyday life - estimates indicate that 80% of Big Data is in fact text data. There is therefore a strong industrial interest in exploiting Big Text problems, and a significant need for Highly Qualified Personnel trained in Big Text Analytics techniques. Our proposal is based on five pillars: (1) a structured curriculum combining the necessary know-how, including "soft skills", in demand by industry, into a novel, specialized Graduate Certificate; (2) hands-on training in the form of an industrial internship for the students with companies such as IBM, Media Miser or Sales Force; (3) national and international student mobility and exchange; (4) a bilingual and multi-lingual application and training environment; (5) respect for privacy as a value instilled in our students and in our approach to Big Data. The combination of these pillars will provide unique, industrially-relevant graduate training of HQP in an area of unmet high demand in Canada and globally. The program involves three strong Canadian Computer Science departments at Dalhousie University (the lead applicant), Université de Montréal and Simon Fraser University. Students who will fulfil all the course and internship requirements will obtain a Graduate Certificate in Big Text Analytics. The Graduate Certificate will be an additional qualification granted to students who will satisfy the TRIBE requirements in the course of their Ph.D. or M.Sc. training. We expect this will attract additional HQP to TRIBE. We provide credible predictions of the strong industrial need for the profile of TRIBE graduates in the years to come, define an innovative curriculum providing technical skills, professional skills, and industrial and research components of the program. The applicants represent a strong team with significant experience in creating and leading inter-institutional, innovative graduate degrees.