摘要
针对移动用户行为序列的情景感知特性,提出一种基于情景感知的行为转移模式推荐算法MPRC。该算法首先采用Apriori对用户历史行为数据进行长度为2的频繁模式的挖掘过滤,然后将过滤后的行为数据转换成决策表,采用粗糙集规则提取对决策表进行处理,挖掘情景转移模式,最后通过模式匹配及情景相似性计算进行推荐排序。实验结果证明了该算法在移动环境下的模式挖掘及推荐方面的有效性和较高的准确性。
In view of the context awareness feature of the mobile user’s behavior sequence, this paper proposes a behaviortransfer pattern recommendation algorithm MPRC. This algorithm uses Apriori to filter the data of user’s historical behaviorin order to obtain a frequent pattern with length 2, and then converts these data into the decision tables for using rule extractionmethod of rough set to process the decision tables to mine context awareness transfer pattern. Finally, MPRC uses patternmatching method and contextual similarity calculation to rank the pattern and to make recommendation. Experimentalresults show that this algorithm is more effective and more accurate in user behavior pattern mining and recommendationin mobile environment.
作者
张晓滨
李园园
ZHANG Xiaobin;LI Yuanyuan(College of Computer Science, Xi’an Polytechnic University, Xi’an 710048, China)
出处
《计算机工程与应用》
CSCD
北大核心
2016年第20期163-166,共4页
Computer Engineering and Applications
基金
陕西省教育厅科学研究计划(No.14JK1307)
关键词
情景感知
行为转移模式
情景相似性
context awareness
behavior transfer pattern
contextual similarity
