【摘要】：針對拖網(wǎng)算法存在的發(fā)現(xiàn)Web社區(qū)數(shù)量過多、社區(qū)間頁面重復(fù)率較高以及嚴(yán)格的社區(qū)定義形成孤立社區(qū)等問題,提出一種基于形式概念分析(FCA)的博客社區(qū)發(fā)現(xiàn)算法。根據(jù)博客網(wǎng)絡(luò)之間的鏈接關(guān)系構(gòu)造概念格,通過格的代數(shù)消解對原始概念格進(jìn)行等價(jià)劃分,度量每個(gè)劃分中概念間外延和內(nèi)涵的結(jié)構(gòu)相似性進(jìn)而合并社區(qū)核心形成社區(qū)。實(shí)驗(yàn)結(jié)果表明:測試數(shù)據(jù)集中社區(qū)核心的網(wǎng)絡(luò)密度大于40%的占全部的83.420%,合并社區(qū)的網(wǎng)絡(luò)直徑為3,且社區(qū)內(nèi)容豐富程度得到提高。所提算法可以有效地運(yùn)用于博客、微博等社交網(wǎng)絡(luò)的社區(qū)發(fā)現(xiàn),具有顯著的應(yīng)用價(jià)值和現(xiàn)實(shí)意義。
[Abstract]:In order to solve the problems such as excessive number of Web communities, high page repetition rate among communities and strict community definition to form isolated communities, a blog community discovery algorithm based on formal concept analysis (FCA) is proposed. The concept lattice is constructed according to the link relation between the blog network, and the original concept lattice is divided by algebraic deconstruction of the lattice, and the structural similarity of the extension and connotation among the concepts in each partition is measured, and then the community core is merged to form the community. The experimental results show that the network density of the community core in the test data set is more than 40%, the network diameter of the merged community is 3, and the richness of the community content is improved. The proposed algorithm can be effectively applied to social networks such as blog, Weibo and so on, which has significant application value and practical significance.
【作者單位】： 蘇州大學(xué)計(jì)算機(jī)科學(xué)與技術(shù)學(xué)院;
【基金】：國家自然科學(xué)基金資助項(xiàng)目(61070122)
【分類號】：TP393.092

【參考文獻(xiàn)】

相關(guān)期刊論文 前4條

1 楊楠,弓丹志,李_，

本文編號：2194710