A semantic search engine based on morphology processing to improve Arabic search - Barbar, Aziz; Ismail, Anis (International Journal of Engineering and Technology, 2019)
In this paper, improving retrieval from Arabic text is tackled. A number of techniques such as truncating, stemming, and morphological analyzers have been introduced into to improve the retrieval performance in search engines. In Arabic search engines, three methods are mainly used: word, stem, and root. The word method is based only on term matching, while the other two methods use morphological anal-ysis. The two methods have different levels of morphological analysis, however, each of these has its limitations. For example, the word and stem methods may miss some relevant records that may contain morphological variations of the targeted word. On the other hand, the root method will always retrieve irrelevant records because it extracts the root from the word, and then searches for all possible morphologi-cal variations of that word. The limitations of the current search methods have motivated this research to investigate a new method to be used in Arabic search engines. This approach is called Semantic Search based on Morphological Processing. This method is based on se-mantic links of the morphological forms. The aim of introducing this method is based on the hope that this method will improve the effec-tiveness of the word and stem methods in terms of retrieving more relevant records. At the same time, it is also hoped that the proposed method will improve the root method by rejecting the irrelevant records that may be retrieved by the root method. A morphology analysis algorithm was designed and proposed to provide the needed stem and pattern extraction with high precision. The proposed algorithm targets modern Arabic text that is not discretized and may contain some faults in spelling. The proposed algorithm is rule-based and can solve all Arabic morphological variations.Â Â