| 面向可信服务选取的基于声誉的推荐者发现方法 |
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| 引用本文： | 潘静,徐锋,吕建.面向可信服务选取的基于声誉的推荐者发现方法[J].软件学报,2010,21(2):388-400. |
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| 作者姓名： | 潘静 徐锋 吕建 |
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| 作者单位： | 南京大学,计算机软件新技术国家重点实验室,江苏,南京,210093;南京大学,计算机软件研究所,江苏,南京,210093 |
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| 基金项目： | Supported by the National Natural Science Foundation of China under Grant Nos.60603034, 60736015, 60721002 (国家自然科学基金); the National Basic Research Program of China under Grant No.2009CB320702 (国家重点基础研究发展计划(973)); the National High-Tech Research and Development Plan of China under Grant Nos.2007AA01Z140, 2007AA01Z178, 2009AA01Z117 (国家高技术研究发展计划(863)); the Jiangsu Provincial Natural Science Foundation of China under Grant No.BK2008017 (江苏省自然科学基金) |
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| 摘 要： | 为了满足开放系统的高度动态性,特别是系统在线演化对服务评估高效性提出的要求,提出了一种基于声誉的推荐者发现方法,首先引入一个相关因子量化不同上下文中的推荐信任关系,得到信任可传递空间,然后应用信任子网分割算法得到评估发起者的可信推荐者群,最后通过主体群内的信任传递与迭代计算,确定具有高声誉值的推荐信息源.初步实验结果表明,该方法有助于在保证推荐信息准确性基础上减少信息收集中的网络资源消耗,从而有效提高可信服务评估的效率.
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| 关 键 词： | 信任 服务选取 声誉 协同推荐 |
| 收稿时间： | 2009/6/15 0:00:00 |
| 修稿时间： | 2009/12/7 0:00:00 |
Reputation-Based Recommender Discovery Approach for Service Selection |
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| Abstract: | Since online system evolution requires efficient service selection to meet with the high dynamics demand of open system, this paper proposes a reputation-based recommender discovery approach. It qualifies trust relationships in different recommendation contexts via a relative factor, divides the Web of trust into personalized trust networks by applying a segment algorithm and finally locates recommenders with high reputation through trust opinion iteration among users. Simulation results show that the suggested approach in this paper helps to reduce the cost in information collection as well as improve the efficiency and precision of service selection results. |
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| Keywords: | trust service selection reputation collaborative recommendation |
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