用户行为与遗传算法相结合的用户兴趣获取  

Users’ Interests Gaining of Combining Users’ Behaviors and GA

作　　者：何兴无[1,2] 朱征宇[1] 曾凡超[1] 邓欣[1] 苑昆峰[1] 

机构地区：[1]重庆大学计算机学院,重庆400044 [2]成都农业科技职业学院电子信息学院,成都611130

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)

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.

关 键 词：遗传算法 适应度函数 用户兴趣 用户模型 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]