基于改进野草算法的推荐对象建模技术研究 |
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引用本文: | 梅创社,;马新慧. 基于改进野草算法的推荐对象建模技术研究[J]. 黑龙江电子技术, 2014, 0(8): 56-58 |
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作者姓名: | 梅创社, 马新慧 |
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作者单位: | [1]陕西工业职业技术学院,陕西咸阳712000; [2]陕西邮电职业技术学院,陕西咸阳712000 |
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基金项目: | 成阳市科学技术研究发展计划项目(2012k07-09);陕西省教育厅科研计划项目(14JK2024)资助 |
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摘 要: | 为了提高个性化推荐系统中模型描述的准确性,提出了一种改进的入侵野草优化算法。该算法将野草算法和混合遗传算法有机地结合,旨在克服传统野草算法过旱收敛、易于陷入局部优化的不足。最后,计算机仿真结果表明了所提出的算法明显优于其他常见的建模算法。
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关 键 词: | 推荐系统 建模 野草算法 混合遗传算法 |
Research on recommended item modeling based on modified invasive weed optimization algorithm |
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Affiliation: | MEI Chuang-she, MA Xin-hui ( 1. Shaanxi Polytechnic Institute, Xianyang 712000, Shaanxi Province, China; 2. Shaanxi Post & Telecommunication College, Xianyang 712000, Shaanxi Province, China) |
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Abstract: | In order to improve the accuracy of model profile within the personahzecl recommenoersystem, this paper proposes a modified invasive weed optimization (MIWO) algorithm. The proposedalgorithm combines IWO algorithm with hybrid generic algorithm (HGA) aiming to avoid over-speedconvergence and involving local optimization. In last section, computer simulation results show that theproposed algorithm is more effective than other optimization algorithms. |
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Keywords: | - recommender system modeling invasive weed optimization ( IWO ) algorithm hybridgeneric algorithm (HGA) |
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