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The paper presents a recommendation model for developing new smart city and smart health projects. The objective is to provide recommendations to citizens about smart city and smart health startups to improve entrepreneurship and leadership. These recommendations may lead to the country's advancement and the improvement of national income and reduce unemployment. This work focuses on designing and implementing an approach for processing and analyzing tweets inclosing data related to smart city and smart health startups and providing recommended projects as well as their required skills and competencies. This approach is based on tweets mining through a machine learning method, the Word2Vec algorithm, combined with a recommendation technique conducted via an ontology-based method. This approach allows discovering the relevant startup projects in the context of smart cities and makes links to the needed skills and competencies of users. A system was implemented to validate this approach. The attained performance metrics related to precision, recall, and F-measure are, respectively, 95%, 66%, and 79%, showing that the results are very encouraging.

Intelligent Recommendations of Startup Projects in Smart Cities and Smart Health Using Social Media Mining