基于超赋值理论的模糊位置描述形式化与推理机制

Formal Representation and Reasoning Mechanism for Vague Spatial Location Description based on Supervaluation

基于位置描述进行空间定位是大数据时代位置服务向智能化转型的关键。针对不同语境中位置描述模糊性差异显著而难以定位的问题,本文提出一种面向模糊位置描述的形式化方法与推理机制。首先,通过梳理人类空间认知规律,明确自然语言中位置描述时关注的要素类型,研究模糊位置描述的形式化表示。然后,基于超赋值理论,从空间对象、距离关系和方向关系3个方面构建模糊位置描述的推理机制。顾及位置描述的上下文语义,利用观察值阈值开展空间推理实现定位。最后,设计收集位置描述的问答系统对方法进行验证。结果表明,本文方法能够依据实际应用场景及时调整位置描述的形式化表示粒度,空间推理结果贴合直观认知。

Location description is the natural language expression of human spatial cognition.Since natural language is the primary and basic means of information transmission in human society,location description is an important medium for transmitting spatial location information in human communication.Spatial positioning based on spatial location description is the key to intelligent transformation of location-based services in the era of big data.To solve the problem that the vagueness of location description in different contexts is significantly different and results in difficulty in positioning,this paper proposes a representation method and reasoning mechanism for vague location description.Firstly,by combing the law of human spatial cognition,the types of elements concerned in the description of natural language are clarified.Based on the analysis of the sources of vagueness,a formal representation of vague location description is constructed.Different from the traditional spatial information modeling which focuses on spatial relationship,the formal representation proposed in this paper establishes the vagueness relation and influence among different information factors by the strategy of multi-factors representation.The formal representation also enhances the semantic analysis ability for the vagueness of location description.Secondly,based on supervaluation theory,the reasoning mechanism of vague location description is proposed from three aspects:spatial object,distance relation,and direction relation.Considering the context semantics of spatial location description,the threshold of observation value is used to carry out spatial reasoning.By being super-valued to different contexts,the reasoning results in different situations are obtained.The aim of the reasoning mechanism is to establish the mapping relationship between vague location description and real spatial location.Thirdly,a Question-Answering(QA)system is designed to collect contexts of location description,and a case study on the method is conducted.In the case study,a group of users'viewpoints from QA on spatial cognition are transformed into the spatial scope in the real world.These spatial scopes can establish the relationship between qualitative spatial concepts and quantitative spatial data,so as to realize the representation of vague location description in GIS.The results show that the proposed method in this paper can adjust the granularity of formal representation of location description in time according to actual application scenarios,and the spatial reasoning results fit intuitive cognition.In the future,knowledge graphs will be introduced to further improve the semantic reasoning ability and positioning accuracy for vague location description.