摘要
为降低旅游路线制定的盲目性与随机性,解决海量旅游信息导致旅游路线选择困难的问题,提出基于改进协同过滤技术的个性化旅游线路推荐方法。根据旅游者拍摄的照片分析旅游者实际旅游足迹,得到旅游点热度,根据旅游点热度确定两个旅游者间的偏好一致度,得到旅游者近邻。根据近邻在各旅游点的浏览时间确定旅游点偏好程度,采用余弦计算方法确定近邻对旅游点偏好程度与旅游者对旅游点偏好程度的偏差值,构建基于用户的协同过滤模型。为防止基于用户的协同过滤模型中冷启动与数据稀疏性问题发生,将基于用户的协同过滤模型和基于地理位置的旅游路线推荐模型相结合,配合旅游者与旅游点地理位置信息,推荐满足旅游者偏好的个性化旅游路线。旅游路线推荐结果显示,所提方法在基于旅游者当前位置向旅游者推荐个性化旅游路线的同时,可确保线路中不存在路线交叉往返现象,降低行程花费时间1 h左右。
In order to reduce the blindness and randomness of tourist route formulation and solve the problem of tourist route selection difficulty caused by massive tourist information,a personalized tourist route recommendation method based on improved collaborative filtering technology is proposed. The tourist actual footprints are analyzed according to the photographs taken by tourists to get hot tourist spots. The preference consistency between two tourists is determined according to the tourist spots ′hot degree to get the two tourists′ approximation. The preference degree of tourist spots is determined according to the approximation in sightseeing time for each tourist spot. The cosine calculation method is used to determine deviation value of the approximation′ s preference degree to a tourist spot and tourists′ preference degree to a tourist spot. The collaborative filtering model based on user is constructed. In order to prevent cold start and data sparsity in the user-based collaborative filtering model,the user-based collaborative filtering model and the location-based tourism route recommendation model are combined to realize the personalized tourist route recommendation that meet the preferences of tourists in combination with the geographic location information of tourists and tourist spots. The results of tourist route recommendation show that the proposed method can not only recommend personalized tourist routes to tourists based on their current location,but also ensure that there is no cross-trip phenomenon in the routes.
作者
艾静超
AI Jingchao(Shenyang Institute of Engineering,Shenyang 110036,China)
出处
《现代电子技术》
北大核心
2019年第23期182-186,共5页
Modern Electronics Technique
基金
沈阳工程学院校内科研立项(RWYB-1506)~~
关键词
个性化旅游
线路推荐
协同过滤
偏好程度
偏差确定
偏好确定
personalized tourism
route recommendation
collaborative filtering
preference degree
deviation determination
preference determination
作者简介
艾静超(1979—),女,辽宁锦州人,硕士,讲师,主要从事教育教学管理及旅游研究。
