摘要
针对兴趣偏向度识别准确率较低,推荐过程稳定性较差的问题,提出语言识别下的数据库信息个性化推荐算法。利用数据库的内部信息分析附属资源连接点,对数据库进行分类标签,确定待推荐标签,利用余弦值计算数据频率,通过匹配信息实现聚类分析,计算兴趣偏向度,得到个性推荐化特点;基于语音识别技术,分层分析数据库信息概念,研究数据库内信息概念关系隶属,经过数据筛选、数据分析、数据输出完成识别过程。实验结果表明,该算法具有较高的稳定性和识别准确性,实际应用效果较好。
In order to solve the problems of low recognition accuracy of interest bias and low stability of recommendation process,a personalized recommendation algorithm for database information based on language recognition is proposed.The internal information of the database is used to analyze the connection points of affiliated resources,and the database is classified and labeled to determine the tags to be recommended.The cosine value is used to calculate the data frequency,and the matching information is used to realize cluster analysis,calculate the interest bias,and obtain the personalized recommendation characteristics.Based on speech recognition technology,the concept of database information is hierarchically analyzed,the relationship between the concept of information in the database is studied,and through data screening,data analysis,data output,the recognition process is completed.The experiment results show that the algorithm has high stability and recognition accuracy,and the practical application effect is guaranteed.
作者
刘品洁
LIU Pin-jie(Luoyang Vocational College of Science and Technology,Luoyang 471000,Henan Province,China)
出处
《信息技术》
2022年第8期191-196,共6页
Information Technology
关键词
语音识别技术
数据库信息
信息个性化类
推荐算法
协同滤波
speech recognition technology
database information
personalization of information
recommendation algorithm
collaborative filtering
