@@ -38,11 +38,11 @@ First of all, we look for a suitable [data set](#dataset). It is important here
We chose the Student essay corpus as our data set. The dataset is provided by the [TU Darmstadt](https://www.tu-darmstadt.de/)
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[This](https://www.informatik.tu-darmstadt.de/ukp/research_6/data/argumentation_mining_1/argument_annotated_essays_version_2/index.en.jsp) is the version we used for our project. <br> The dataset consist of 404 argumentative essays. Each essay has a different topic and ends with a summary paragraph. Since this last paragraph contains all the necessary information about the text, we consider only that one in our project. The essays are already split by the editor into train and test.
[This](https://www.informatik.tu-darmstadt.de/ukp/research_6/data/argumentation_mining_1/argument_annotated_essays_version_2/index.en.jsp) is the version we used for our project. <br> The dataset consist of 404 argumentative essays covering a wide array of topics. Each essay has a different topic and ends with a summary paragraph. Since this last paragraph contains all the necessary information about the text, we consider only that one in our project. The essays are already split by the editor into train and test.
## Tools
#### ConceptNet
> ConceptNet is a freely-available semantic network, designed to help computers understand the meanings of words that people use.
> ConceptNet is a freely-available semantic network, designed to automatically discover frames and labels based on topic modeling.
ConceptNet originated from the crowdsourcing project Open Mind Common Sense, which was launched in 1999 at the MIT Media Lab. It has since grown to include knowledge from other crowdsourced resources, expert-created resources, and games with a purpose. ~ quoted from [here](https://conceptnet.io/)
