CAJ | 학술논문

在空间数据库中点、线段和区域是构成向量对象的三种基本实体。现有的索引结构能够将点或区域对象有效地组织成散列或分层目录，并且提供精确的检索方法。然而，这些索引结构索引线段时会出现以下问题。索引结构不能准确地表示线段的空间信息，这将阻碍对线段空间数据的高质量存储。位于层次目录中节点之间将产生大量死空间和重叠区域，随着时间的推移这将降低系统性能。提出一种采用数据压缩的索引结构CB树。与R树索引结构相比，CB树具有较优查询效率，占用较少存储空间。
재공간수거고중점、선단화구역시구성향량대상적삼충기본실체。현유적색인결구능구장점혹구역대상유효지조직성산렬혹분층목록，병차제공정학적검색방법。연이，저사색인결구색인선단시회출현이하문제。색인결구불능준학지표시선단적공간신식，저장조애대선단공간수거적고질량존저。위우층차목록중절점지간장산생대량사공간화중첩구역，수착시간적추이저장강저계통성능。제출일충채용수거압축적색인결구CB수。여R수색인결구상비，CB수구유교우사순효솔，점용교소존저공간。
Point, line and region are three basic entities which constitute vector-based objects in spatial databases. Exist-ing index structures can effectively organize the objects such as points, regions into hash or hierarchical directory, and pro-vide accurate retrieval methods. However the following questions arise when such methods are applied to line segments. Spatial information of line segments may not be precisely expressed which impedes high-quality conservation of line seg-ments. In the hierarchical directory, a lot of dead space and overlapping regions will be generated between nodes, which degrade the performance over time. The paper presents the index structure CB-tree based on data compression. Compared with R-tree, CB-tree has optimum query efficiency, takes up less storage space.