%0 Journal Article
%T Research of searching strategy in topic crawler using dynamical particle swarm optimization<br>基于动力粒子群算法的网络蜘蛛搜索策略研究*
%A TONG Ya-la
%A LI Yuan-xiang
%A SHEN Xian-jun
%A <br>童亚拉
%A 李元香
%A 沈显君
%J 计算机应用研究
%D 2008
%I 
%X Traditional topic crawler,which uses monistic searching strategy,may cause the problems of topic drift,not utilizing structural information and being easy to miss searching direction.This paper proposed a new heuristic searching algorithm based on dynamical PSO,which considered the characteristics of Web structure and synthesized the advantage of linkage's immediate value and future value,especially could dynamically adjust the weight between the two rewards online.The kind of crawler was adaptive.The experiments show that this algorithm had better performance in recall rate and precision compared with some traditional algorithms.
%K topic crawler
%K Web community
%K dynamical PSO
%K immediate value
%K future value<br>网络蜘蛛
%K Web社区
%K 动力粒子群
%K 立即价值
%K 未来价值
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=0C473AA1C1357520459528DF024D8CC2&yid=67289AFF6305E306&vid=C5154311167311FE&iid=94C357A881DFC066&sid=2A46E9718B53247E&eid=CB8F7B3BEDA8D32B&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=19