| KEYWORD |
Using trending topic in Online Social Networks for recommendation systems
keywords BIG DATA ANALYSIS, DATA SCIENCE, GRAPHS, MACHINE LEARNING, MODELLING, NLP, RECOMMENDER SYSTEMS, STATISTICS
Reference persons MARTINO TREVISAN, LUCA VASSIO
External reference persons Greta Vallero (DET)
Research Groups SmartData@PoliTO, Telecommunication Networks Group
Thesis type DATA ANALYSIS
Description The candidate will build on top of previous work from the research group and will design and engineer a real-time analyzer of social networks (Facebook and Instagram) to extract trending topics and provide these to a recommendation system. The student will use large quantities of data from social networks. The data will be organized and analyzed using big data techniques (such as Pyspark). Then, the student will improve a current methodology to dynamically extract trending topics and the words/sentences that characterize them. These will be used to search within a catalogue of items for recommender systems. The student will also analyze the performance evaluation of the whole engineered system. Possibly, a dynamic web interface will be published to provide results to the public.
Required skills Data analysis, python programing, preferentially big data (pyspark), machine learning, graphs
Notes Contact luca.vassio@polito.it
Deadline 20/04/2024
PROPONI LA TUA CANDIDATURA