The information fusion field has recently been attracting a lot of interest within the scientific community, as it provides, through the combination of different sources of heterogeneous information, a fuller and/or more precise understanding of the real world than can be gained considering the above sources separately. One of the fundamental aims of computer systems, and especially decision support systems, is to assure that the quality of the information they process is high. There are many different approaches for this purpose, including information fusion. Information fusion is currently one of the most promising methods. It is particularly useful under circumstances where quality might be compromised, for example, either intrinsically due to imperfect information (vagueness, uncertainty, …) or because of limited resources (energy, time, …). In response to this goal, a wide range of research has been undertaken over recent years. To date, the literature reviews in this field have focused on problem-specific issues and have been circumscribed to certain system types. Therefore, there is no holistic and systematic knowledge of the state of the art to help establish the steps to be taken in the future. In particular, aspects like what impact different information fusion methods have on information quality, how information quality is characterised, measured and evaluated in different application domains depending on the problem data type or whether fusion is designed as a flexible process capable of adapting to changing system circumstances and their intrinsically limited resources have not been addressed. This paper aims precisely to review the literature on research into the use of information fusion techniques specifically to improve information quality, analysing the above issues in order to identify a series of challenges and research directions, which are presented in this paper.

信息融合领域最近在科学界引起了很多兴趣，因为它通过不同来源的异构信息的组合提供了对现实世界的更全面和/或更精确的理解，而不是考虑到上述情况。分别来源。计算机系统，尤其是决策支持系统的基本目标之一是确保它们处理的信息质量很高。为此有许多不同的方法，包括信息融合。信息融合是目前最有前途的方法之一。它在质量可能受到损害的情况下特别有用，例如，由于信息不完善（模糊、不确定等）或资源有限（能源、时间等）。为了实现这一目标，近年来进行了广泛的研究。迄今为止，该领域的文献综述都集中在特定问题上，并且仅限于某些系统类型。因此，没有全面和系统的现有技术知识来帮助确定未来要采取的步骤。特别是，不同的信息融合方法对信息质量的影响，如何根据问题数据类型在不同的应用领域中表征、测量和评估信息质量，或者融合是否被设计为能够适应不断变化的系统的灵活过程等方面情况及其本质上有限的资源没有得到解决。