CAJ | 학술논문

数据库深度查询的难点在于如何以最优匹配度实现数据匹配。传统数据库查询方法采用关键字匹配方法，在单一条件下效果较佳，但是当查询条件较多时，查询效率低且匹配度差。提出了一种基于多元特征K分布融合的数据库深度查询方法，通过数据库分元方法设置多元，在多元分布基础上，提取多元分布的每个特征，成为多元特征集合，通过对多元特征集合的K分布特征融合，实现数据查询特征的深度融合，降低查询条件冗余度，提高查询效率。采用实际数据库进行查询测试实验，结果显示，基于K分布特征融合的数据库深度查询方法，查询效率提高了35%，具有应用价值。
수거고심도사순적난점재우여하이최우필배도실현수거필배。전통수거고사순방법채용관건자필배방법，재단일조건하효과교가，단시당사순조건교다시，사순효솔저차필배도차。제출료일충기우다원특정K분포융합적수거고심도사순방법，통과수거고분원방법설치다원，재다원분포기출상，제취다원분포적매개특정，성위다원특정집합，통과대다원특정집합적K분포특정융합，실현수거사순특정적심도융합，강저사순조건용여도，제고사순효솔。채용실제수거고진행사순측시실험，결과현시，기우K분포특정융합적수거고심도사순방법，사순효솔제고료35%，구유응용개치。
The difficult of database query was how to query the database with the best match of data. In the conventional method, a database query keyword matching method was used, it worked preferably under the effect of a single condition, but when there were more conditions, the effect was poor. A depth database query method was proposed based on K distri-bution of multi-feature fusion, through a database of diverse settings element method, on the basis of multivariate distribu-tions, multivariate distributions of each feature extraction, the feature became pluralistic, the feature was set by the K-dis-tribution feature fusion method, the data query features was deeply integrated, the query redundancy was greatly reduced and the query efficiency was improved. The actual database queries were used to do the test experiments, and the results show that with K distribution of multi-feature fusion, the query efficiency is greatly improved by 35%, it has good applica-tion value.