GA-based Parameter Optimization For Word Segmentation
| dc.contributor.author | Ammar Mohamed Ammar | |
| dc.date.accessioned | 2025-06-15T07:04:22Z | |
| dc.date.issued | 2017-05 | |
| dc.description.abstract | Word segmentation is the process of finding the best likely sequence of words from a sequence of concatenated characters without spaces. Several re- searches proposed solutions to word segmentations using heuristic methods. The main task of the last methods is to hopefully find the best segmentation without searching the entire state spaces. This paper proposes a new approach for word segmentation based on parameters optimization by means of Genetic Algorithm. The approach is tested on English language using two different language models taking into consideration several data sets. To show that the presented approach is domain language independent, the approach is experimented furthermore on the Arabic language. The experiments show that segmentation using parameters optimization gives a better results | |
| dc.identifier.uri | https://research.arabeast.edu.sa/handle/123456789/40 | |
| dc.language.iso | en | |
| dc.publisher | Artificial Intelligence and Machine Learning | |
| dc.title | GA-based Parameter Optimization For Word Segmentation | |
| dc.type | Article |