發(fā)布時(shí)間：2018-08-25 20:04

【摘要】：隨著云計(jì)算的發(fā)展,互聯(lián)網(wǎng)上涌現(xiàn)出越來越多的功能相同但服務(wù)質(zhì)量(QoS)不同的Web服務(wù).基于服務(wù)質(zhì)量的服務(wù)推薦,旨在從這些等功能服務(wù)中挑選出滿足用戶服務(wù)質(zhì)量需求的服務(wù),已成為服務(wù)計(jì)算領(lǐng)域的一個(gè)熱門課題.由于極少有用戶曾調(diào)用過所有候選服務(wù),推薦系統(tǒng)將面臨服務(wù)質(zhì)量缺失的問題,因此,基于協(xié)同過濾的思想,提出一種服務(wù)質(zhì)量預(yù)測算法RST.與以往算法相比,RST算法利用反向預(yù)測機(jī)制解決數(shù)據(jù)稀疏問題,提高了預(yù)測準(zhǔn)確度.此外,RST算法基于用戶對推薦結(jié)果的反饋,自動(dòng)建立與維護(hù)信任度模型,可動(dòng)態(tài)改善預(yù)測效果.最后,基于真實(shí)的數(shù)據(jù)集,驗(yàn)證RST預(yù)測算法的效果,并衡量各參數(shù)對預(yù)測結(jié)果的影響.
[Abstract]:With the development of cloud computing, more and more Web services with the same function but different quality of service (QoS) emerge on the Internet. Service recommendation based on quality of Service (QoS), which aims to select services from these functional services to meet the needs of users, has become a hot topic in the field of service computing. Because very few users have ever called all candidate services, the recommendation system will face the problem of missing quality of service. Therefore, based on the idea of collaborative filtering, a quality of service prediction algorithm RST. is proposed. Compared with the previous algorithms, the RST algorithm uses reverse prediction mechanism to solve the problem of data sparsity, and improves the accuracy of prediction. In addition, based on the user feedback to the recommended results, the RST algorithm automatically establishes and maintains the trust model, which can dynamically improve the prediction results. Finally, based on the real data set, the effectiveness of the RST prediction algorithm is verified, and the influence of various parameters on the prediction results is measured.
【作者單位】： 浙江大學(xué)計(jì)算機(jī)學(xué)院;
【基金】：國家科技支撐計(jì)劃項(xiàng)目(2011BAH16B04)資助 國家自然科學(xué)基金項(xiàng)目(61173176)資助 浙江省科技項(xiàng)目(2008C03007)資助 國家“八六三”高技術(shù)研究發(fā)展計(jì)劃項(xiàng)目(2011AA010501)資助
【分類號】：TP393.09

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