Linguistic computational techniques based on hesitant fuzzy linguistic term set (HFLTS) have been swiftly advanced on various fronts over the past five years. However, one critical issue in the existing theoretical development is that modeling possibility distribution based semantics involves a relatively strict constraint that linguistic terms are uniformly distributed across an HFLTS. Releasing the constraint of uniform HFLTS through which individual semantics could be customized is challenging yet intriguing for participants interested in this topic. Comparative linguistic expressions (CLEs) generated from context-free grammar facilitate flexible and accurate linguistic elicitation, and in consideration of computational simplicity, are transformed into HFLTSs that are machine manipulatable. It is imperative that the precision of customized individual semantics can be significantly improved with respect to different CLEs. This study proposes a novel possibility computation structure for HFLTS possibility distributions based on the linguistic terms similarity measure. The uniquely established linguistic terms in each and every CLE are initially treated as referential items for comparison. Then, possibilities of linguistic terms in a transformed HFLTS can be calculated as their similarity degrees to the predetermined referential item. Subsequently, the interweaving method in which a consistent inner interweaving matrix needs to be constructed is adopted for attitudinal characters to attain appealing degrees characterized in the unit interval. The generated attitudinal HFLTS possibility distributions provide a solution to the problem of modeling individually the semantic implications of CLEs. Several illustrative examples and comparative analyses further demonstrate that individual semantics endowed with attitudinal character model efficiently individual differences in cognitive styles.

中文翻译：

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为具有态度 HFLTS 可能性分布的个体定制语义


过去五年来，基于犹豫模糊语言术语集（HFLTS）的语言计算技术在各个领域得到了迅速发展。然而，现有理论发展中的一个关键问题是，基于语义的可能性分布建模涉及相对严格的约束，即语言术语在 HFLTS 中均匀分布。对于对此主题感兴趣的参与者来说，释放统一 HFLTS 的约束（通过该约束可以定制单个语义）具有挑战性，但也很有趣。由上下文无关语法生成的比较语言表达（CLE）有利于灵活、准确的语言启发，并且考虑到计算的简单性，被转换为机器可操作的 HFLTS。对于不同的 CLE，定制的个体语义的精度必须能够显着提高。本研究提出了一种基于语言术语相似性度量的 HFLTS 可能性分布的新颖可能性计算结构。每个CLE中独特建立的语言术语最初被视为比较的参考项目。然后，可以将变换后的HFLTS中的语言术语的可能性计算为它们与预定参考项的相似度。随后，态度特征采用需要构造一致的内部交织矩阵的交织方法，以达到单位区间表征的吸引力程度。生成的态度 HFLTS 可能性分布为单独建模 CLE 的语义含义的问题提供了解决方案。 几个说明性例子和比较分析进一步证明，态度特征模型赋予的个体语义有效地反映了认知风格的个体差异。