41 lines
970 B
Markdown
41 lines
970 B
Markdown
# ANLP_WS24_CA2
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# Master MDS Use NLP techniques to analyse texts or to build an application. Document your approach.
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## TODOS
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data
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- maybe buffer zone between good and bad jokes (trade off would be less data)
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- maybe not bineary classification
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- maybe change to humor detection (more data available)
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- dataset shape doesnt work correctly
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- history: integrate validation loss
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## Data
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https://competitions.codalab.org/competitions/27446
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https://aclanthology.org/2021.semeval-1.9.pdf#:~:text=HaHackathon%20is%20the%20first%20shared%20task%20to%20combine,its%20average%20ratings%20for%20both%20humor%20and%20offense.
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- Hackathon: https://homepages.inf.ed.ac.uk/s1573290/data.html
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## Data embeddings
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- gloVe 6B tokens: https://nlp.stanford.edu/projects/glove/
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#### Not Prioritised (Pun data)
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- Challenge https://alt.qcri.org/semeval2017/task7/
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- Pun Annotated Amazon (joke not included ...): https://github.com/amazon-science/expunations/tree/main/data
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