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The availability of videos has grown rapidly in recent years. Finding and browsing relevant information to be automatically extracted from videos is not an easy task, but today it is an indispensable feature due to the immense number of digital products available. In this paper, we present a system which provides a process to automatically extract information from videos. We describe a system solution that uses a re-trained OpenNLP model to locate all the places and famous people included in a specific video. The system obtains information from the Google Knowledge Graph related to relevant named entities such as places or famous people. In this paper we will also present the Automatic Georeferencing Video (AGV) system developed by RAI (Radiotelevisione italiana, which is the national public broadcasting company of Italy, owned by the Ministry of Economy and Finance) Teche for the European Project "La Città Educante" (The Educating City: teaching and learning processes in cross-media ecosystem) Our system contributes to The Educating City project by providing the technological environment to create statistical models for automatic named entity recognition (NER), and has been implemented in the field of education, in Italian initially. The system has been applied to the learning challenges facing the world of educational media and has demonstrated how beneficial combining topical news content with scientific content can be in education. [ABSTRACT FROM AUTHOR]

This study develops an optimization model for bus transit network based on road network and zonal ODM (Origin Destination Matrix). The source information has been obtained via recorded phone data of transit users collected by an Italian telecommunication operator.The model aims at achieving minimum bus transfers and maximum passenger flow per unit length with line length and non-linear rate as constraints. An operations research algorithm is used to solve the problem (ACS). To further optimize results, the model uses Google APIs for traffic optimization. The model is tested with survey data of Rome city. The results show that an optimized bus network with less transfers and travel time can be obtained, and the application of operations research algorithm effectively increases the calculation speed and quality. [ABSTRACT FROM AUTHOR]