Arabic is ranked as the seventh largest language on the Internet but it has also been the fastest growing language in the last decade in terms of users. At this rate of growth, Arabic users should have the fourth largest user population on the Internet by 2020. Given these facts, it is not surprising that Arabic Information Retrieval (IR) has garnered significant attention. The main research interests have focused on retrieval of formal language, mostly in the news domain, with ad hoc retrieval, OCR document retrieval, and cross-language retrieval. The literature on other aspects of retrieval continues to be sparse or non-existent, though some of these aspects have been investigated by industry. Others aspects of Arabic retrieval that have received attention include document image retrieval, speech search, filtering, and social media and web search. However, efforts within different aspects of Arabic retrieval continue to be deficient and severely lacking behind efforts in other languages. Arabic Information Retrieval reviews Arabic IR including the nature of the Arabic language, the techniques used for pre-processing the language, the latest research in Arabic IR in different domains, and the open areas in Arabic IR. It covers general properties of the Arabic language, aspects of Arabic that affect retrieval, Arabic processing necessary for effective Arabic retrieval, Arabic retrieval in public IR evaluations, Arabic IR and NLP resources, and specialized retrieval problems such as Arabic-English CLIR, Arabic Document Image Retrieval, Arabic Social Search, Arabic Web Search, Question Answering, Image retrieval, and Arabic Speech Search. Lastly, it also discusses open IR problems that require further attention.