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.

翻译：近年来，信息融合领域在科学界引起了广泛关注，因为通过融合不同来源的异构信息，它能够提供比单独考虑上述来源更全面和/或更精确的现实世界理解。计算机系统，尤其是决策支持系统的基本目标之一是确保其处理的信息质量较高。为此存在多种不同方法，信息融合便是其中之一。信息融合是目前最具前景的方法之一，在信息质量可能受损的情况下尤为有用，例如因信息本身不完善（模糊性、不确定性）或资源有限（能量、时间）而导致质量下降的情况。围绕这一目标，近年来开展了广泛的研究。迄今为止，该领域的文献综述多聚焦于特定问题，且局限于某些系统类型。因此，目前缺乏全面系统的前沿知识来帮助确定未来应采取的研究步骤。具体而言，以下方面尚未得到充分探讨：不同信息融合方法对信息质量的具体影响；在不同应用领域中如何根据问题数据类型来表征、度量和评估信息质量；以及融合过程是否被设计为能够适应系统环境变化及其固有资源限制的灵活流程。本文旨在系统综述专门为提升信息质量而采用信息融合技术的研究文献，通过分析上述问题，识别出一系列挑战与研究方向，并在文中予以阐述。