摘要
尽管已经有一些遗传算法被应用于获取用户兴趣,但如何帮助用户找到最符合用户兴趣的信息,仍然存在诸多问题。好的适应度函数对于改善获取用户兴趣的遗传算法是非常重要的。该文设计了一个新的用于获取用户兴趣的遗传算法的适应度函数,使用该函数的遗传算法有效地提高了获取用户兴趣的准确性,减轻了用户的负担。通过实验,验证了该算法的有效性和优越性。
Though there already exist some GAs which have been desiged to gain users' interests , it is still difficult for users to find their special information. Surely, a good fitness function is very important for improving the effect of the genetic algorithm to gain users' interests. A new fitness function is proposed by using this new fitness function. The accurity is improved considerably and the users feel more easy when they use the personalization system. The experiment has proved the superiority and effectiveness of the algorithm proposed by this paper.
出处
《微处理机》
2008年第4期89-91,95,共4页
Microprocessors
基金
高校博士学科点专项科研基金资助课题(20030611016)
关键词
遗传算法
适应度函数
用户兴趣
用户模型
Genetic algorithm
Fitness function
User interest
User profile