基于小数据决策的读者兴趣发现与预测
发布时间：2018-11-05 19:35
【摘要】：【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。
[Abstract]:The reader's reading interest can be divided into short-term interest and long-term interest. As the basis and core of library personalized service push, the reader's interest discovery model is the key to the effectiveness of library's personalized service, and its accuracy and timeliness are the key to the effectiveness of the library's personalized service. At present, the readers' reading behavior information is collected, the tacit knowledge is excavated and the readers' reading interest is gained. It has become an important research direction of library personalized service. [method / process] this paper presents a model of reader's interest discovery and prediction based on small data decision making. [results / conclusions] A model of reader's interest discovery and prediction based on small data decision is proposed. Testing and analysis of data, It can enhance the accuracy of forecasting the service demand of readers, improve the efficiency of the recommendation of personalized service, improve the quality of personalized service, and meet the needs of personalized service of readers.
【作者单位】： 兰州财经大学信息中心;兰州财经大学电子商务综合实验室;
【分类号】：G252
，
本文编号：2313158
[Abstract]:The reader's reading interest can be divided into short-term interest and long-term interest. As the basis and core of library personalized service push, the reader's interest discovery model is the key to the effectiveness of library's personalized service, and its accuracy and timeliness are the key to the effectiveness of the library's personalized service. At present, the readers' reading behavior information is collected, the tacit knowledge is excavated and the readers' reading interest is gained. It has become an important research direction of library personalized service. [method / process] this paper presents a model of reader's interest discovery and prediction based on small data decision making. [results / conclusions] A model of reader's interest discovery and prediction based on small data decision is proposed. Testing and analysis of data, It can enhance the accuracy of forecasting the service demand of readers, improve the efficiency of the recommendation of personalized service, improve the quality of personalized service, and meet the needs of personalized service of readers.
【作者单位】： 兰州财经大学信息中心;兰州财经大学电子商务综合实验室;
【分类号】：G252
，
本文编号：2313158
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