Design and development of a semantic search engine for videolectures
External reference persons Canale Lorenzo
Thesis type EXPERIMENTAL, RESEARCH
Description The thesis aims at creating and validating a key topic serach system for videolecture content in the context of the educational services of Politecnico di Torino.
The objective is to improve effectiveness and ease of use of the educational video service provided to students, through the implementation of a semantic search engine working for all the published videolectures. This engine, given a string that contains a sentence related to the video lecture content, should provide a list of videos and timeframes where the teacher deals with this content.
The main involved research areas are Learning Analytics, Machine learning and Semantic Web. The preferred programming language is Python, and the main machine learning libraries will be used: Numpy, Pandas, Scikit-learn, Keras.
Once the search engine will be implemented and validated, it will be integrated in the services of the Educational Portal of Politecnico di Torino.
Required skills CapacitÓ di programmazione (linguaggi di alto come Python o simili).
Basic comptence on machine learning is welcome, but not required.
Deadline 01/10/2019 PROPONI LA TUA CANDIDATURA