Formal concept analysis (FCA) has been widely studied as an important tool for data processing and knowledge discovery. The present work focuses on FCA under uncertainty while the attributes are described with linguistic terms or attribute description are incomplete. Accordingly, a linguistic concept formal context is introduced first. With an attempt of knowledge reduction, the multi-granularity similarity relationship between linguistic concepts is defined on the basis of granular computing which further divides the linguistic concept set into three parts under λ-granularity (i.e., core linguistic concept, unnecessary linguistic concept, and relative necessary linguistic concept). A multi-granularity linguistic reduction algorithm of incomplete linguistic concept formal context is then introduced. To handle the incompleteness, a new algorithm to complete the incomplete linguistic concept formal context based on the closeness degree between fuzzy objects is proposed. Finally, based on the Boolean matrix and Boolean factor analysis method, the linguistic concept knowledge reduction algorithm to extract the core linguistic concept and reduce the scale of linguistic concept lattice is proposed to handle the complexity, which is achieved by computing the similarity of linguistic concept knowledge in order to handle different types of linguistic information and concept knowledge. The effectiveness and practicability of the proposed model are illustrated by examples.

形式概念分析（FCA）已被广泛研究为数据处理和知识发现的重要工具。当前的工作集中在不确定性下的FCA，而用语言术语描述属性或属性描述不完整。因此，首先介绍语言概念形式语境。为了减少知识，尝试在粒度计算的基础上定义语言概念之间的多粒度相似关系，该关系将λ语言粒度下的语言概念集进一步分为三部分（即核心语言概念，不必要的语言概念和相对必要的语言概念）。然后介绍了一种不完整语言概念形式上下文的多粒度语言归约算法。为了处理不完整，提出了一种基于模糊对象之间的接近度来完成不完整语言概念形式语境的新算法。最后，基于布尔矩阵和布尔因子分析方法，提出了一种语言概念知识约简算法，用于提取核心语言概念并减小语言概念格的规模，以处理复杂性，这是通过计算语言概念的相似度来实现的。为了处理不同类型的语言信息和概念知识。实例说明了该模型的有效性和实用性。提出了一种语言概念知识约简算法，以提取核心语言概念，并减少语言概念格的规模，以解决复杂性问题。该算法是通过计算语言概念知识的相似度来处理不同类型的语言信息和概念知识而实现的。 。实例说明了该模型的有效性和实用性。提出了一种语言概念知识约简算法，以提取核心语言概念并减少语言概念格的规模，以解决复杂性问题。该算法是通过计算语言概念知识的相似度来处理不同类型的语言信息和概念知识而实现的。 。实例说明了该模型的有效性和实用性。