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Design and implementation of personalized search model on user's interest

机译:用户兴趣的个性化搜索模式的设计与实现

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The traditional information retrieval technology can not satisfy the personalized queries. To solve this problem, we have researched and improved the standard BP algorithm to find user's potential demands, and finally an improved BP neural network algorithm based on personalized search method is proposed. The experiment shows that the algorithm can effectively enhance BP algorithm convergent speed and avoid falling into local minimum, and significantly improve the recommendation quality of the personalization system.
机译:传统信息检索技术无法满足个性化查询。 为了解决这个问题,我们已经研究和改进了标准的BP算法,找到了用户的潜在需求,最后提出了一种改进的基于个性化搜索方法的神经网络算法。 实验表明,该算法可以有效地提高BP算法会聚速度,避免落入局部最小值,并显着提高个性化系统的推荐质量。

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