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【目的/意义】读者的阅读兴趣可分为短期兴趣和长期兴趣,具有不稳定性。读者兴趣发现模型作为图书馆个性化服务推送的基础和核心,其准确性和时效性是图书馆个性化服务有效的关键。当前,采集读者的阅读行为信息,从中挖掘隐性知识并获取读者的阅读兴趣,已成为目前图书馆个性化服务一个重要的研究方向。【方法/过程】本文提出了一种基于小数据决策的读者兴趣发现与预测模型。【结果/结论】通过对读者小数据的测试和分析,可增强图书馆对读者服务需求预测的精度,提升图书馆个性化服务推荐的效率,改善图书馆个性化服务的质量,满足读者的个性化服务需求。
[Purpose / Significance] Reader’s reading interest can be divided into short-term interests and long-term interests, with instability. The reader interest discovery model, as the foundation and core of the library personalized service delivery, is the key to the effective library personalization service. At present, collecting reader’s reading behavior information, mining tacit knowledge and gaining reader’s reading interest has become an important research direction of personalized service in current libraries. [Method / Process] This paper presents a reader-interest discovery and prediction model based on small data decisions. [Results / Conclusion] By testing and analyzing the reader’s small data, the library can enhance the accuracy of the service demand prediction of the readers, improve the efficiency of personalized service recommendation of the library, improve the quality of the personalized service of the library and meet the reader’s personality Service needs.