面向对象的文化景观基因概念格算法

An Object-oriented Algorithm for Constructing the Conceptual Lattice of Cultural Landscape Genes of Traditional Settlements

文化景观基因(简称景观基因)是反映传统聚落丰富的历史文化信息与传统文化特征的功能单元,在推动传统聚落保护及其优秀文化资源的深度开发与利用方面有着广泛的应用前景。针对结合空间数据挖掘方法分析传统聚落景观特征的相关研究缺乏,论文结合概念格空间数据挖掘原理提出了景观基因概念格。在此基础上,通过将传统聚落定义为对象,将景观基因定义为概念格的属性,论文设计了面向对象的景观基因概念格分层构造算法(Object-oriented Layered Conceptual Lattice,OOLCL)。论文选取湖南省现存的30个保存较为完好的历史文化名村和名镇为实验对象,同时与经典的Bordat算法进行对比,以此测试OOLCL算法的性能。结果表明,在属性数量大于对象数量的条件下,OOLCL算法通过对象与对象两两之间属性的交集运算减少了算法冗余度,平均时间耗费减少66.61%,显著提升了概念格的构造效率。这说明OOLCL算法能较好地适用于复杂的传统聚落文化要素特征及其相互关系的判别与分析处理,本文对今后结合GIS和空间数据挖掘方法分析传统聚落的重要传统文化特征具有较好的借鉴意义。

In order to enhance the high-quality development,accelerate China-style modernization,and promote the dissemination of Chinese civilization,numerous traditional Chinese settlements and historical villages and towns with abundant historical cultural information have garnered unprecedented attention.It becomes imperative to mine the rich traditional knowledge and core cultural features from these traditional settlements to meet existing social needs.Cultural Landscape Genes of Traditional Settlements(CLGTS)are generally regarded as the basic units of the abundant historical-cultural information and traditional cultural characteristics within traditional settlements.CLGTS has attracted wide concerns from the scholars and has been extensively employed to deal with various issues on traditional settlements,such as preservation,tourism development plan,and sustainable development.However,there is still a lack of research on using spatial data mining methods and theories to reveal the core cultural features of traditional settlement landscapes.To address this issue,based on the principles of conceptual lattices,this study proposes the CLGTS-conceptual lattice.This lays a solid theoretical foundation for developing an algorithm capable of addressing the complex relationships of various CLGTS.In this study,we develop a novel conceptual lattice algorithm“Object-oriented Layered Conceptual Lattice(OOLCL)”that treats the traditional settlements as objects and defines the CLGTS as the properties of conceptual lattice.In order to evaluate the performance and efficiency of OOLCL,we carry out an experiment with 30 historical-cultural famous villages and towns in Hunan Province,which are well-preserved and popular among tourists due to the distinctive characteristics of traditional cultures.Additionally,we also compare OOLCL with the typical Bordat algorithm which is a commonly used method for constructing conceptual lattice.In our algorithm,when the properties(CLGTS)outnumber objects(traditional settlements),OOLCL can reduce the redundant nodes and data significantly by conducting intersection calculation between objects and thus enhance the efficiency of conceptual lattice construction.According to the theoretical findings and experimental results in this study,OOLCL holds significant implications for advancing research on the key traditional cultural characteristics of traditional Chinese settlements by combining GIS and spatial data mining methods.