With the rapid growth in use of mobile devices, more and more mobile generated data is in great need of processing. A large amount of valuable content exists in natural text such as web pages, news feeds, SMS, and Twitter/WeChat messages. Natural language processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) language texts. NLP aims to provide a computer program with the ability to process and understand unstructured texts. In the mobile environment, NLP can make apps smarter by automatically analyzing the meaning of content and taking appropriate actions on behalf of their users. The state-of-the-art NLP techniques have proven to be useful in dealing with the information overload problem in the mobile environment, for example, news aggregation and summarization, question answering, information extraction and retrieval, semantic understanding, and personalization.

Using NLP techniques in the context of mobile devices has recently gained attention, among both academic and industry communities. Efforts have been made to develop various NLP applications for mobile platforms, such as retrieving information about places or events like Siri or context-sensitive information extraction like Google Now. However, it still lacks deep text processing capabilities, such as abstraction, summarization, and semantic understanding. Moving beyond the common applications, in the fast growing area such as healthcare, critical electronic health record data is accessible almost anywhere and near instantly in ICU. Patient notes can be recalled with a few taps on a screen. The apparent needs for the more complex information-intensive tasks that require sophisticated NLP analysis are increasing.

In this special issue, articles regarding the use of technologies, methodologies, and applications for natural language processing and mobile computing are invited. The special issue will be expected to show a diversity of new developments in these areas. Authors are encouraged to submit high-quality original research articles as well as review articles mainly describing original research and presenting results that advance the state of the art.

Potential topics include but are not limited to the following:

• NLP techniques for the personalization of mobile users
• NLP empowered mobile applications
• NLP assisted information extraction and retrieval for mobile environment
• NLP assisted information aggregation, abstraction, and summarization for mobile environment
• NLP solutions for capturing mobile users’ interests
• Question answering technologies for smart environment
• NLP systems for mobile environment
• NLP techniques for mobile health
• Smart solutions for semantic understanding
• Case studies, field trials, and research projects on NLP enhanced systems for mobile environment
• Machine learning models for NLP in mobile environments
• Research trends and challenges in NLP empowered mobile services