Abstract
The explosion of mostly unstructured data has further motivated researchers to focus on Natural Language Processing (NLP), hereby encouraging
the development of Information Extraction (IE) techniques that target the retrieval of crucial information from unstructured texts. In this paper we present a
literature review on Open Information Extraction (OIE). We compare both machine learning and handcrafted rules-based algorithmic approaches and identify
the recently proposed Neural OIE approach as a particularly promising area for
further research.
the development of Information Extraction (IE) techniques that target the retrieval of crucial information from unstructured texts. In this paper we present a
literature review on Open Information Extraction (OIE). We compare both machine learning and handcrafted rules-based algorithmic approaches and identify
the recently proposed Neural OIE approach as a particularly promising area for
further research.
| Original language | English |
|---|---|
| Title of host publication | 30th Benelux Conference on Artificial Intelligence |
| Subtitle of host publication | BNAIC 2018 Preproceedings |
| Editors | M. Atzmueller, W. Duivesteijn |
| Publisher | Springer |
| Pages | 223–234 |
| Publication status | Published - 2018 |
Keywords
- Open Information Extraction
- Deep Learning
- Machine Learning
- Hand-crafted Rules
- Shallow Syntactic Analysis