基于模拟退火法的概念集构造算法  

Construction Algorithm of Concept Set Based on Simulated Annealing Algorithm

作　　者：刘忠慧[1] 陈建宇 宋国杰[2,3] 闵帆 LIU Zhonghui;CHEN Jianyu;SONG Guojie;MIN Fan(School of Computer Science,Southwest Petroleum University,Chengdu 610500;School of Sciences,Southwest Petroleum University,Chengdu 610500;Institute for Artificial Intelligence,Southwest Petroleum University,Chengdu 610500)

机构地区：[1]西南石油大学计算机科学学院,成都610500 [2]西南石油大学理学院,成都610500 [3]西南石油大学人工智能研究院,成都610500

出　　处：《模式识别与人工智能》2021年第8期723-732,共10页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金面上项目(No.41674141)资助。

摘　　要：在形式概念分析中,构造概念格需要较高的时空复杂度,但仅部分格或概念集用于推荐应用.针对上述问题,文中提出基于模拟退火法的概念集构建算法.首先,提出候选概念生成技术,目标函数考虑概念外延相似度,解的更新采用Metropolis准则.再提出概念筛选技术,以外延相似度为评价指标,选择每位用户的强概念构成集合.最后,提出推荐技术,利用外延中邻居用户的偏好,向目标用户提供个性化推荐.在5个公开数据集上的实验表明,文中算法的推荐效果和效率较优.In formal concept analysis,the construction of concept lattice produces high time and space complexity,but only partial lattices or concept sets are applied in recommendation.To solve this problem,a construction algorithm of concept set based on simulated annealing algorithm is proposed.The candidate concepts generation technique is presented based on the simulated annealing algorithm.The objective function takes the extension similarity of a concept into account.The Metropolis criterion is employed to update the solution.The concept filtering technique is designed based on all candidate concepts.Strong concepts of each user are selected with the extension similarity as the evaluation indicator,and the filtered strong concepts constitute a concept set.The recommendation technique is proposed based on the strong concept set.It provides personalized recommendations to the target user using the preferences of neighbor users in the same extension.Experimental results on 5 public datasets demonstrate that the recommendation performance and the efficiency of proposed algorithm are superior.

关 键 词：形式概念分析 模拟退火算法 概念集 外延相似度 个性化推荐 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]