摘要
在面向实体推荐的探究过程中,包含多样属性的实体获得了越来越多的关注。然而,在面对这种复杂实体对象的推荐过程中,当前的研究工作者大多选用其中一种属性,利用相关算法得以实现。在基于分类处理的方法,对推荐实体的属性进行了深入探究,将物品属性网络划分为多个子信息网络。在子信息网络中,以属性数目为界,将子网络中的多属性以及单属性转化为实体相似度的多样途径,结合实体相似度以及相关算法,得出推荐结果。最后通过实验验证本文的算法,引用多样属性不仅体现了推荐多样性,还提高了推荐精度。
In the process of exploring entity recommendation, the entity containing diverse attributes has gained more and more attention. Most of the current researchers mainly select one attribute, and embody it in the related algorithms and their extensions even though the entity is combined with multiple attributes in entity recommendation. In this paper, on the basis of the classification method, we delve into physical properties of the recommended entities, divide entity＇s attribute information network into multiple sub ones. In sub information network, bounded by the amount of attributes, the single attribute and even multiple attributes can be diverted into diverse paths of entity similarity, combining with entity similarity and related algorithm, where we can get the recommended results. This study not only refers to various attributes, but also improves the precision of recommendation.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2018年第2期405-413,共9页
Journal of System Simulation
基金
国家科技支撑计划(2014BAK15B01)
关键词
实体推荐
多样属性
分类
相似度途径
entity recommendation
multiple attribution
classification
similarity path
