
Tokenization is a fundamental task focused on text processing. Among other tasks, the segmentation process is used to identify information units, such as sentences and words. In this paper, we discuss the Natural Language ToolKit (NLTK) tokenizer as a step to manipulate patterns within text. The purpose of this work is to build up Natural Language Processing (NLP) base for Jawi corpus. A series of experiments was performed, to validate the corpus and fulfill the requirement of the Jawi script tokenizer, with the promising results. Based on these promising results, the token will be used for tagging process.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
