| publication name | Hierarchical N-gram Algorithm for extracting Arabic Entities |
|---|---|
| Authors | E Amer, HM Khalil, T El-shistawy |
| year | 2016 |
| keywords | Natural Language Processing; Entity; N-gram; Arabic Wikipedia; Information Extraction |
| journal | |
| volume | Not Available |
| issue | Not Available |
| pages | Not Available |
| publisher | Not Available |
| Local/International | International |
| Paper Link | Not Available |
| Full paper | download |
| Supplementary materials | Not Available |
Abstract
Entities Extraction becomes very important for developing many applications of Natural Language Processing (NLP). In this paper, we present a new algorithm to extract entities from Arabic text. The approach uses the semi-structured knowledge source: Arabic Wikipedia to predict the words that constitutes an Arabic entity. Our method is generic and can be applied directly to other languages to extract entities. The proposed method has been designed to analyze Arabic text hierarchically with variable length N-gram. The experimental results have proven that the proposed system is very efficient in detecting entities from large set of Arabic news