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International audienceThe shift in human computer interaction from desktop computing to mobile interaction highly influences the needs for new designed interfaces. In this paper, we address the issue of searching for information on mobile devices, an area also known as Mobile Information Retrieval. In particular, we propose to summarize as much as possible the information retrieved by any search engine to allow universal access to information

Natural language processing (NLP) refers to the field of study that focuses on the interactions between human language and computers. It has recently gained much attention for analyzing human language computationally and has spread its applications for various tasks such as machine translation, information extraction, summarization, question answering, and others. With the rapid growth of cloud computing services, merging NLP in the cloud is a significant benefit. It allows researchers to conduct NLP-related experiments on large amounts of data handled by big data techniques while harnessing the cloud’s vast, on-demand computing power. However, it has not sufficiently spread its tools and applications as a service in the cloud and there is little literature available that discusses the scope of interdisciplinary work. NLP, cloud Computing, and big data are vast domains and contain their challenges and potentials. By overcoming those challenges and integrating these fields, great potential for NLP and its applications can be unleashed. This paper presents a survey of NLP in cloud computing with a key focus on the comparison of cloud-based NLP services, challenges of NLP and big data while emphasizing the necessity of viable cloud-based NLP services. In the first part of this paper, an overview of NLP is presented by discussing different levels of NLP and components of natural language generation (NLG), followed by the applications of NLP. In the second part, the concept of cloud computing is discussed that highlights the architectural layers and deployment models of cloud computing and cloud-hosted NLP services. In the third part, the field of big data in the cloud is discussed with an emphasis on NLP. Furthermore, information extraction via NLP techniques within big data is introduced.

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