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Data-to-text systems are powerful in generating reports from dataautomatically and thus they simplify the presentation of complex data. Ratherthan presenting data using visualisation techniques, data-to-text systems usenatural (human) language, which is the most common way for human-humancommunication. In addition, data-to-text systems can adapt their output contentto users' preferences, background or interests and therefore they can bepleasant for users to interact with. Content selection is an important part ofevery data-to-text system, because it is the module that determines which fromthe available information should be conveyed to the user. This survey initiallyintroduces the field of data-to-text generation, describes the generaldata-to-text system architecture and then it reviews the state-of-the-artcontent selection methods. Finally, it provides recommendations for choosing anapproach and discusses opportunities for future research.

Content Selection in Data-to-Text Systems: A Survey