摘要
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。
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.
出处
《科技通报》
北大核心
2015年第4期215-217,221,共4页
Bulletin of Science and Technology
基金
广东省高等学校优秀青年教师培养计划资助(Yq2013171)
构建中高职衔接的职业能力标准的研究与实践-以工科类专业为依托(20120201011)
