基于小数据决策的读者兴趣发现与预测

Discovering and Predicting Reader Interests Based on Small Date Decision Support

【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 interests can be categorized into short-term interests and long-term interests, and may evolve over time.As the basis and core of the personalized service recommendation in library, the accuracy and effi- ciency of the user-interest discovery model is a key to the personalized service of library. Nowadays, it is an important re- search direction of personalized reading service of library to collect readers＂ reading behavior information resource for min- ing implicit knowledge and obtaining the reader interests. [ Method/process ] This paper proposed a discovering and predict- ing model for reader interests based on small date decision support. [Result/conclusion] Through testing and analysis on small data of reader, it can improve the prediction precision of reader service demand forecast, enhance the recommenda- tion efficiency of personalized service in library, improve quality of personalized service of library, and satisfy readers per- sonalized service needs.