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Seminar on Internet Technologies (Summer 2023) (view source)

Revision as of 14:28, 8 March 2023

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| Social Media Comments Network
| Explainable AI(XAI) / graph neural network (XGNN)
| In this topic, you will study methods to crawl the dataset from social networks and utilize social science network analysis in any topic you are interested in (science/education/politics…) to find out the network structure and compare the difference among different topics.
| In this topic, students study how AI models / GNNs are explained with SOTA papers.
| Basic programming knowledge
| Basic AI / GNN knowledge
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
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| Yes
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| Analysis of MOOC Discussion Forum
| Social Media Comments Network (Intern/Project/Thesis possible)
| In this topic you will study methods to crawl the dataset from MOOCs and evaluate if the active users have more influence on overall forum activities and the evaluation of the course.
| In this topic, you will study methods to crawl the dataset from social networks(e.g. YouTube) and utilize social science network analysis in any topic you are interested in (science/education/language…) to find out the network structure and compare the difference among different topics.
| Basic programming knowledge
| Python skills (Data crawling, cleaning, statistical data analysis, modeling and visualization), basic graph knowledge
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
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| No
| Yes
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| The life-circle of vanished scientific journals (Intern/Project/Thesis possible)
| In this topic, students will mine the information of vanished/(ongoing)/top journals, try to find out the difference features(manually/ML-based method) between journals facing different destinies.
| Python skills (Data Crawling, Cleaning, EDA, Modeling). Basic graph, XAI knowledge is a plus.
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
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| Yes
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| Traffic prediction with GNN (Intern/Project/Thesis possible)
| In this topic, students will study how to use XGNN to predict traffic volumn.
| Strong Python skills (Modeling and Visualization). Graph and XAI knowledge.
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
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| Yes
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| ML/DL based industrial equipment predictive maintenance (Intern/Project/Thesis possible)
| In this topic, students will study how to use cutting-edge machine learning models to predict when industrial equipment need to be maintained before crashing.
| Strong Python skills (Cleaning, EDA, Modeling and Visualization). XAI knowledge is a plus.
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
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| Yes
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| Open topics
| Open topics in Data Science & Applied Statistics, especially XAI
| Depends
| [Zhengze Li, zhengze.li@cs.uni-goettingen.de]
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| Yes
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