摘要
当前旅游景区推荐系统软件部分的推荐规则不明确,导致推荐准确率下降,为此本文设计了基于规则推理的旅游景区推荐系统.在原有系统硬件基础上对软件部分进行优化设计,建立旅游景区空间信息分布式检索模型,采用子块分析方法对检索到的信息进行重构和关联规则分析,通过模糊规则推理方法提取信息的相似度和差异度特征量,根据差异度水平设计旅游景区推荐决策过程,采用自适应寻优方法进行旅游景区推荐决策过程的智能寻优.仿真结果表明,采用该方法进行旅游景区推荐的自适应性较好,推荐准确性较高,能够有效满足旅游景区智能化推荐的需求.
At present,the recommendation rules of the software part of the scenic spot recommendation system are not clear,which leads to the decline of the recommendation accuracy.Therefore,this paper designs a scenic spot recommendation system based on rule-based reasoning.On the basis of the original system hardware,the software part is optimized,the spatial information distributed retrieval model of tourist attractions is established,the retrieved information is reconstructed and the association rules are analyzed by using the sub block analysis method,the similarity and difference characteristics of information are extracted by using the fuzzy rule reasoning method,the recommendation decision-making process of tourist attractions is designed according to the difference level,and the self It adapts to the optimization method to carry out intelligent optimization in the process of scenic spot recommendation decision-making.The simulation results show that the proposed method is adaptive and accurate,and can effectively meet the needs of intelligent recommendation.
作者
马莉娟
蔡鲲鹏
张松婷
MA Lijuan;CAI Kunpeng;ZHANG Songting(College of History,Culture and Tourism,Fuyang Normal University,Fuyang Normal University,Fuyang 236000,China;College of Computer and Information Engineering,Fuyang 236000,China)
出处
《商丘师范学院学报》
CAS
2021年第3期7-10,共4页
Journal of Shangqiu Normal University
基金
阜阳师范大学校级重点教学研究项目“高等师范院校旅游管理专业课程资源开发与培养模式构建——基于研学导师的培养”(2019JYXM15)
阜阳师范大学人文社科研究项目“基于粗糙集和熵权法的城市旅游目的地综合评价研究”(2018FSSK05ZD)。
关键词
规则推理
旅游景区
推荐
智慧化
特征提取
大数据
rule reasoning
tourist attractions
recommendation
intelligence
feature extraction
big data
