[1]康晓凤,邵晓根.基于遗传算法的智能商品搜索策略的研究[J].南京师大学报(自然科学版),2014,37(04):126.
 Kang Xiaofeng,Shao Xiaogen.Study of Intelligent Goods Search Strategies Based on Genetic Algorithm[J].Journal of Nanjing Normal University(Natural Science Edition),2014,37(04):126.
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基于遗传算法的智能商品搜索策略的研究()
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《南京师大学报(自然科学版)》[ISSN:1001-4616/CN:32-1239/N]

卷:
第37卷
期数:
2014年04期
页码:
126
栏目:
计算机科学
出版日期:
2014-12-31

文章信息/Info

Title:
Study of Intelligent Goods Search Strategies Based on Genetic Algorithm
作者:
康晓凤邵晓根
徐州工程学院信电学院,江苏 徐州 221008
Author(s):
Kang XiaofengShao Xiaogen
Department of Information and Electrical Engineering,Xuzhou Institute of Technology,Xuzhou 221008,China
关键词:
搜索引擎智能遗传算法自然编码
Keywords:
search engineintelligencegenetic algorithmnatural coding
分类号:
TP20
文献标志码:
A
摘要:
电子商务购物系统为我们的日常生活带来了极大的便利,但是,随着现有电子商务购物系统中商务信息的急剧增加,导致用户搜索耗时太长,影响了交易的顺利进行.为解决这种问题,提出了基于遗传算法的智能搜索策略.首先根据用户输入的初始搜索字段,利用实数编码构造进化个体.然后提出了基于用户行为的个体适应函数值的评价模型,辅助用户尽快搜索到满意商品.最后基于Java平台开发了智能搜索引擎,通过与传统搜索引擎在搜索耗时和成功率方面的比较验证了该方法的有效性.
Abstract:
The e-commerce shopping systems have greatly offered benefits to our daily life,however,the systems developed now often make the user spend a lot of time finding the satisfactory goods in e-commerce due to the increasing of commerce information.An Intelligent search strategies based on Genetic Algorithm is proposed to overcome the above shortages.Firstly,a natural coding was designed to encode the goods according to their key words and the ones entered by the user.Then,For effectively comparing the satisfied degree of the user on all displayed goods,a fitness function was built based on the goods the user had evaluated.Lastly,a personalized search strategy with Java was developed and compared with the traditional Search Strategy,and the results show that our algorithm is obviously advanced in saving user time and improving trade success.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2014-08-16.
基金项目:科技部技术创新项目(13C262132018660)、江苏省科技计划项目(BC2010058)、徐州工程学院2012科研项目(XKY2012308).
通讯联系人:康晓凤,讲师,研究方向:智能计算和信息安全.E-mail:kxfeng07@163.com
更新日期/Last Update: 2014-12-31