本文關(guān)鍵詞：雙目標(biāo)優(yōu)化的RDF圖分割算法　出處：《計(jì)算機(jī)工程與應(yīng)用》2017年21期 　論文類型：期刊論文

  更多相關(guān)文章： RDF圖 靜態(tài)分割 動(dòng)態(tài)分割 邊割 負(fù)載均衡

【摘要】：分布式存儲(chǔ)是解決大規(guī)模數(shù)據(jù)存儲(chǔ)的一種比較有效的方法,而數(shù)據(jù)分割是實(shí)現(xiàn)分布式存儲(chǔ)的前提。面對不斷增長的RDF數(shù)據(jù),提出一種基于雙目標(biāo)優(yōu)化的RDF圖分割算法(RDF Graph Partitioning algorithm based on Double Objective Optimization,RGPDOO)。RGPDOO將邊割和分割平衡兩項(xiàng)圖分割指標(biāo)融合到一個(gè)目標(biāo)函數(shù),并依據(jù)此目標(biāo)函數(shù),實(shí)現(xiàn)了RDF圖的靜態(tài)和動(dòng)態(tài)分割。其中靜態(tài)圖分割通過對圖進(jìn)行初始劃分,將圖中頂點(diǎn)分成內(nèi)核頂點(diǎn)、交叉頂點(diǎn)和自由頂點(diǎn)三類。然后通過計(jì)算目標(biāo)函數(shù)增益對交叉和自由頂點(diǎn)進(jìn)行分配。動(dòng)態(tài)圖分割部分,針對RDF元組的插入和刪除給出相應(yīng)的解決方案。同時(shí),為了滿足圖分割目標(biāo),算法每隔一段時(shí)間T會(huì)根據(jù)子圖的平衡性和緊密性進(jìn)行一次動(dòng)態(tài)調(diào)整。實(shí)驗(yàn)選擇合成和真實(shí)數(shù)據(jù)集進(jìn)行測試,并分別與幾種通用的靜態(tài)和動(dòng)態(tài)圖分割算法進(jìn)行比較。實(shí)驗(yàn)結(jié)果表明提出的算法能夠有效地實(shí)現(xiàn)RDF圖的靜態(tài)和動(dòng)態(tài)分割。
[Abstract]:Distributed storage is a more effective method to solve large-scale data storage, and data segmentation is the premise of distributed storage. Facing the growing RDF data. A two-objective optimization based RDF image segmentation algorithm is proposed. RDF Graph Partitioning algorithm based on Double Objective. Optimization. RGPDOO).RGPDOO merges edge cutting and partition equilibrium into one objective function and according to this objective function. The static and dynamic segmentation of the RDF graph is realized, in which the vertices in the graph are divided into kernel vertices by initial partition of the graph. Crossover vertices and free vertices are divided into three categories. Then the crossover and free vertices are allocated by calculating the objective function gain. The corresponding solution for RDF tuple insertion and deletion is given. At the same time, in order to meet the goal of graph segmentation. Every other time T adjusts dynamically according to the balance and compactness of the subgraph. The experiment chooses the composition and the real data set to test. Compared with several general static and dynamic image segmentation algorithms, the experimental results show that the proposed algorithm can effectively realize the static and dynamic segmentation of RDF images.
【作者單位】： 大連理工大學(xué)軟件學(xué)院;渤海大學(xué)信息科學(xué)與技術(shù)學(xué)院;
【基金】：國家自然科學(xué)基金(No.U1301253,No.61672123) 廣東省科技計(jì)劃(No.2015B010110006) 國家重點(diǎn)研發(fā)計(jì)劃(No.2016YFD0800300) 遼寧省博士科研啟動(dòng)基金項(xiàng)目(No.201601348,No.201601349)
【分類號(hào)】：TP333
【正文快照】： 1引言萬維網(wǎng)聯(lián)盟(W3C)推薦的資源描述框架(ResourceDescription Framework,RDF)是描述語義網(wǎng)中各種資源與它們之間語義關(guān)系的一個(gè)重要框架標(biāo)準(zhǔn)[1]。RDF使用三元組主語,謂語,賓語來描述世界,當(dāng)把主語和賓語看做圖中兩個(gè)頂點(diǎn),謂語看做是由主語指向謂語的有 向邊時(shí),RDF數(shù)據(jù)集

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