CAJ | 학술논문

为了提高数据库检索的智能性及个性化推荐，将改进的ART算法应用于数据库自动知识推荐。首先对基本ART算法及ART网络算法进行了描述，接着提出了改进的ART算法，最后运用实例仿真，验证该算法性能。文本采用某高校数字图书馆数据库作为仿真对象，验证其自动知识推荐的功能，同时对其资源消耗和扫描时间进行了计算仿真，实验证明，本文算法在数据库自动知识推荐过程中，所耗资源少且效率高，具有一定的研究价值。
위료제고수거고검색적지능성급개성화추천，장개진적ART산법응용우수거고자동지식추천。수선대기본ART산법급ART망락산법진행료묘술，접착제출료개진적ART산법，최후운용실례방진，험증해산법성능。문본채용모고교수자도서관수거고작위방진대상，험증기자동지식추천적공능，동시대기자원소모화소묘시간진행료계산방진，실험증명，본문산법재수거고자동지식추천과정중，소모자원소차효솔고，구유일정적연구개치。
In order to improve the intelligent and personalized recommendation of database retrieval, improved ART algorithm is applied to automatic knowledge recommended of database. First describe the basic ART algorithm and ART network algorithm, and then put forward the improved ART algorithm. Finally, take simulation instance to verify the performance of the algorithm. A university digital library database as the simulation object, verify its work of automatic knowledge recommended, and the resource consumption and scanning time are calculated in the simulation. Experiments show that the proposed algorithm in the process of automatically knowledge recommended of database has lower resource consumption and better efficiency, and definitely has research value.