CAJ | 학술논문

高维索引作为基于内容检索和模式识别等领域的一项关键技术，其性能直接影响整个系统的查询速度和准确率，但高维情况下的“维度灾难”一直制约着相应检索性能的提高。通过分析小世界模型，提出了完整的逐跳逼近索引算法，该算法仅维护点与点在度量空间上的局部邻近关系，通过将查询过程的“关注点”逐步往查询命中区域跳跃逼近来实现高维空间数据点间的范围查询和近似近邻查询。实验证明该方法在不依赖索引数据的先验分布情况下能有效地处理高维数据向量的检索，且具有良好的可维护性与拓展性。
고유색인작위기우내용검색화모식식별등영역적일항관건기술，기성능직접영향정개계통적사순속도화준학솔，단고유정황하적“유도재난”일직제약착상응검색성능적제고。통과분석소세계모형，제출료완정적축도핍근색인산법，해산법부유호점여점재도량공간상적국부린근관계，통과장사순과정적“관주점”축보왕사순명중구역도약핍근래실현고유공간수거점간적범위사순화근사근린사순。실험증명해방법재불의뢰색인수거적선험분포정황하능유효지처리고유수거향량적검색，차구유량호적가유호성여탁전성。
High-dimensional indexing is a key technique in content based retrieval and pattern recognition field, and the performance of it affects the retrieval speed and accuracy directly, but Curse of Dimensionality hinders the improvement of it. This paper proposes a high-dimensional indexing technology based on graph which uses small world model as design idea. During the range and the approximate neighbor query, this method gradually approximates the query focuses to the hit area. Experiment demonstrates that this method can handle with the retrieval of high-dimensional data vectors effectively without prior distribution knowledge. And the maintainability and expansibility of this system is also good.