云计算环境下旅游信息适应性自组织推送算法研究

针对当前推送旅游信息质量不高,而无法满足使用者需求的问题,提出一种旅游信息适应性自组织推送方法。通过求出目标使用者和其他使用者之间的相似度,找到目标使用者的最近邻集合。利用模糊遗传算法确定加权函数,通过加权函数实现使用者对旅游项目评分的更新,以适应使用者变化的旅游兴趣。求出目标使用者对某旅游项目兴趣度预测值,将预测值最高的旅游项目推送给使用者。实验结果表明,所提算法推送旅游信息质量高,可满足使用者需求。

Adaptive self organizing push algorithm for tourism information in cloud computing environmen

in the cloud computing environment, user interest in travel over time will change, the traditional tourism information push algorithm does not consider the user changing interest in travel, tourism has the same interest that users, push the tourism information quality is not high, can not meet the needs of users. Therefore, a new adaptive self-organizing push algorithm for tourist information is proposed. This paper introduces the self organizing push process of tourism information. By finding the similarity between the target user and other users, the nearest neighbor set of the target user is found. The weighted function is defined by fuzzy genetic algorithm, and the user"s score of tourism items is updated by weighting function to adapt to the changing tourist interest. Find out the target user"s prediction of the interest degree of a tourist item, and push the highest value of the tourism item to the user. The experimental results show that the proposed algorithm has high quality of travel information and meets the needs of users.