基于室内定位技术的图书馆推荐算法

Indoor positioning technique-based library recommendation algorithm

为解决图书馆推荐系统存在的数据稀疏性问题,帮助读者选择感兴趣的图书,提出基于室内定位的图书馆推荐算法.该算法使用室内定位技术,以书架为定位单元,根据读者在图书馆的活动轨迹,获得读者兴趣偏好,将偏好信息引入基于用户的协同过滤算法,发现兴趣相似读者,进行推荐.实验结果表明,此算法能有效解决图书馆推荐系统中数据稀疏性问题,为读者提供位置相关的个性化图书推荐.

In order to solve the problem of data sparsity in library recommendation system and assist readers to choose books that they are interested in,a library recommendation algorithm this article is presented in based on indoor positioning.In this algorithm,the indoor positioning technique is adopted,the bookshelves selected by the readers are taken as positioning units to track the moving loci of the readers in the library and obtain their interest and preference.Then this information is introduced into user-based collaborative filtering algorithm to discover the readers with similar interest and preference and then recommend the books to them.The experimental result shows that this algorithm can resolve the problem of data sparsity in library recommendation system,providing the position-related personalized book recommendation to the readers.