Non-diacritization is a deeply seated property of the Arabic orthography. Attempts to produce tools to generate diacritics for a general text are underway. Most of the tools developed in this area, concentrate on the making and understanding of the text (sentence) and produce the proper diacritics of a word according to its position in the text. The results of such tools are still at their early stages. It will be quite some time before an efficient general-purpose tool for diacritics generation is produced. The purpose of this paper is to     study substring pattern behaviour in diacritized Arabic names. Pattern behaviour is very important in word prediction and the results can be applied to automatic diacritization and transliteration of Arabic names.

Statistical properties of a natural language are one of the most important parts of language analysis. Number of Different Words (NODW) and Different Word Usage Ratio (DWUR) concepts are some of the general characteristics of a corpus. We have modified this concept to calculate the Number of Different Segments (NODS) and Different Segment Usage Ratio (DSUR) to statistically analyze our corpus of Arabic names. Renewal and clump counts are other statistical metrics that shed light on substring pattern behavior. The names corpus were analyzed for these measures and the results tabulated.