A Corpus Based Approach for the Automatic Creation of Arabic Broken Plural Dictionaries

Research has shown that Arabic broken plurals constitute approximately 10% of the content of Arabic texts. Detecting Arabic broken plurals and mapping them to their singular forms is a task that can greatly affect the performance of information retrieval, annotation or tagging tasks, and many other text mining applications. It has been reported that the most effective way of detecting broken plurals is through the use of dictionaries. However, if the target domain is a specialized one, or one for which there are no such dictionaries, building those manually becomes a tiresome, not to mention expensive task. This paper presents a corpus based approach for automatically building broken plural dictionaries. The approach utilizes a set of rules for mapping broken plural patterns to their candidate singular forms, and a corpus based co-occurrence statistic to determine when an entry should be added to the broken plural dictionary. Evaluation of the approach has shown that it is capable of creating dictionaries with high levels of precision and recall.