An Annotation tool for Natural language processing tasks
| dc.contributor.author | M. Bezza aya M. Maache Nadjet | |
| dc.date.accessioned | 2025-02-10T08:09:11Z | |
| dc.date.available | 2025-02-10T08:09:11Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | This dissertation creates an annotation tool used in Natural Language Processing (NLP) tasks. NLP has the appropriate techniques to exploit valuable information, provided that a large amount of annotated textual data is available. Most annotation processes rely on manually handling a large body of text for development and evaluation. Creating a large annotated corpus is tedious and requires adequate computational support. Although many annotation tools are available, their primary weaknesses lie in their specific purposes and commercial licenses. Since the quality of the data used to train the NLP model directly affects the quality of the results, ensuring quality control of the annotations is essential. To facilitate this process, we have created a tool that helps us to collect comments from social media platforms such as YouTube and Reddit and annotate them. | |
| dc.identifier.uri | http://dspace.univ-khenchela.dz:4000/handle/123456789/7816 | |
| dc.language.iso | en | |
| dc.title | An Annotation tool for Natural language processing tasks | |
| dc.type | Thesis |