一种基于GridGIS的增量式协同过滤算法

计算机科学 ›› 2013, Vol. 40 ›› Issue (12): 219-222.

一种基于GridGIS的增量式协同过滤算法

邸佳奇,王霓虹

哈尔滨师范大学计算机科学与信息工程学院哈尔滨150025;东北林业大学信息与计算机工程学院哈尔滨150040

出版日期:2018-11-16 发布日期:2018-11-16
基金资助:
本文受黑龙江省教育厅科学技术研究项目:基于Android的智能教育资源信息平台构建研究(12531215)资助

Incremental Collaborative Filtering Algorithm Based on GridGIS

DI Jia-qi and WANG Ni-hong

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： 空间数据的广泛应用需要高效的推荐系统来管理,以增加空间数据的可用性。用户协同过滤(Collaborative Filtering)是推荐系统中发展最为迅速的方法之一,也是在电子商务领域应用最广泛的方法。在研究传统协同过滤算法的基础上提出了一种减轻数据稀疏性对推荐效果产生的负面影响的方法。提出了一种基于项目相似度的数据填充方法,其目的在于当原始数据集比较稀疏时为算法提供足够的数据支持。经实验证明,改进算法在空间数据集上比传统方法有更好的预测性能和运行效率。

关键词: GIS,网格计算,GridGIS,协同过滤,增量算法

Abstract: Wide application of spatial data requires an efficient system to manage the recommendation in order to increase the availability of spatial data．Extensive application of spatial data requires an efficient framework to manage,in order to increase the availability of spatial data．Grid geographic information system (GridGIS) supports rapid spatial data retrieval,allowing users to transparently access data at any time in any place．Traditional similarity algorithm is mathematically very rigorous,has somewhat less usefulness and lacks data support．The experiment proves that algorithm in spatial data sets than the traditional method has better prediction performance and operating efficiency．

Key words: GIS,Grid computing,GridGIS,Collaborative filtering,Incremental algorithm

邸佳奇,王霓虹. 一种基于GridGIS的增量式协同过滤算法[J]. 计算机科学, 2013, 40(12): 219-222. https://doi.org/

DI Jia-qi and WANG Ni-hong. Incremental Collaborative Filtering Algorithm Based on GridGIS[J]. Computer Science, 2013, 40(12): 219-222. https://doi.org/

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