摘要：【中文】本发明提供一种休闲农业旅游推荐方法、系统、电子设备及存储介质，方法包括：根据旅游网站上用户对景点的评分信息，用聚类法将信息中的用户划分为不同的群体，把群体的中心值作为未评分项目的填充值，利用相似群体的评分信息初步预测评分；将文本信息输入预先训练的深度合作神经网络，产生景点推荐策略；再通过采集用户当前城市、具有纬度和经度的用户位置、天气等情景感知信息，综合地理距离、天气情况来确定最终推荐列表。本发明采用聚类算法对用户进行聚类，填充未评分项，改善数据稀疏性问题，又通过文本挖掘提升休闲农业旅游推荐效果，最后采用情景感知信息进一步为游客提供个性化的推荐服务。 【EN】The invention provides a leisure agriculture tourism recommendation method, a system, electronic equipment and a storage medium, wherein the method comprises the following steps: according to the scoring information of the scenic spots of the users on the tourist website, dividing the users in the information into different groups by a clustering method, taking the central value of the group as the filling value of the unscored items, and preliminarily predicting scoring by using the scoring information of similar groups; inputting text information into a pre-trained deep cooperation neural network to generate a scenic spot recommendation strategy; and determining a final recommendation list by collecting the current city of the user, the position of the user with latitude and longitude, weather and other context awareness information and integrating the geographic distance and the weather condition. According to the method, the clustering algorithm is adopted to cluster the users, the non-scoring items are filled, the data sparsity problem is improved, the travel recommendation effect of the leisure agriculture is improved through text mining, and finally, the situation awareness information is adopted to further provide personalized recommendation service for tourists.