本文選題：復雜網(wǎng)絡 + 平行算法　； 參考：《復雜系統(tǒng)與復雜性科學》2013年02期

【摘要】：歸納出對在線社交網(wǎng)絡研究具有挑戰(zhàn)性的一些課題,介紹描述用戶關系的邏輯模型(粉絲模型),提出邏輯關系寓意鄰接矩陣(粉絲矩陣)。用此模型展示對微博平臺Top-X信息查詢的聚合-排序-刪除算法。進一步應用映射和化簡概念將上述Top-X信息查詢算法擴展于并行計算環(huán)境,給出映射關注和化簡粉絲在Ha-doop系統(tǒng)聯(lián)機實現(xiàn)的算法。粉絲模型和相應的算法實現(xiàn)了對新浪微博74.7GB和Twitter的101GB實際數(shù)據(jù)的多種約束下信息查詢和微博轉發(fā)預測,特別是在Hadoop系統(tǒng)聯(lián)機環(huán)境下,新方法的信息化簡和計算性能明顯提高。
[Abstract]:This paper summarizes some challenging topics in the research of online social networks, introduces the logical model (fan model) to describe the user relationship, and puts forward the logical relationship implication adjacency matrix (fan matrix). This model is used to demonstrate the aggregation-sort-delete algorithm for Top-X information query on Weibo platform. Furthermore, the concepts of mapping and simplification are applied to extend the above Top-X information query algorithm to the parallel computing environment, and the online implementation algorithm of mapping attention and simplification fans in Ha-doop system is given. The fan model and the corresponding algorithm have realized the information query and Weibo forwarding prediction for the actual 101GB data of Sina Weibo 74.7GB and Twitter under various constraints. Especially in the online Hadoop system, the information simplification and computational performance of the new method have been improved obviously.
【作者單位】： 巴西利亞大學計算機系TransLab實驗室;
【基金】：巴西科學技術發(fā)展委員會(CNPq,304058/2010-6,478039/2012-3)
【分類號】：TP393.0

【參考文獻】

相關期刊論文 前4條

1 楊涵新;汪秉宏;;復雜網(wǎng)絡上的演化博弈研究[J];上海理工大學學報;2012年02期

2 段磊;唐常杰;楊寧;左R，

本文編號：1964070