基于智慧推荐的高校智慧图书馆服务模式研究

发布时间：2018-05-17 02:16

本文选题：智慧推荐 + 智慧图书馆　；参考：《天津理工大学》2017年硕士论文

【摘要】：高校图书馆一直以来都是实现教学辅助与科学研究的服务中心,是学术交流与文化传播的文化中心,是信息传递与数据共享的资源中心,承担着服务读者的重要社会价值。随着“智慧地球”概念的提出,各种新技术的发展以及信息爆炸现象的出现,图书馆的传统服务模式已经无法满足读者用户信息需求,高校图书馆正朝着智慧图书馆的方向前进。智慧推荐能够积极主动挖掘并分析读者用户行为,向读者用户提供量身定制的信息资源推荐服务,满足读者用户日益丰富的多样化新需求。本文通过从智慧推荐角度着手,探讨高校智慧图书馆智慧服务模式,研究设计智慧服务模式框架,增强读者用户对高校图书馆的黏着性,并对智慧推荐的算法提出一定改进和优化。论文的主要工作如下:(1)对国内116所“211”院校进行了智慧推荐服务的实证调查研究,对利用网站访查、问卷调查等方式获得的数据进行综合归纳整理,调查发现,几乎所有高校均提供了部分非个性化服务内容,但高校图书馆距离智慧图书馆尚有很大差距,智慧服务功能人性化、智慧化程度较低,同时过于依赖OPAC系统所提供的附带的简单推荐功能,提供的推荐服务相似且单一。(2)对基于智慧推荐的高校智慧图书馆服务模式从四个角度入手进行了研究设计。主要包括智慧检索服务模式构建、智慧推荐服务模式构建、智慧APP服务模式构建及智慧微媒体服务模式构建。(3)在传统推荐算法基础上做出改进和优化。通过针对高校图书馆读者用户群体的自身特点,构建读者特征模型,生成候选最近邻集,从而产生最近邻集,生成推荐结果,使推荐结果更加匹配读者用户的偏好,以提高推荐结果的准确性,让读者用户对智慧推荐服务产生依赖性,为构建高校智慧图书馆智慧推荐提供一定算法支持。
[Abstract]:The university library has always been the service center of teaching aid and scientific research, the cultural center of academic exchange and cultural communication, the resource center of information transmission and data sharing, and the important social value of serving readers. With the introduction of the concept of "intelligent earth", the development of various new technologies and the emergence of the phenomenon of information explosion, the traditional service mode of library can no longer meet the information needs of readers. University libraries are moving in the direction of intelligent libraries. Intelligent recommendation can actively excavate and analyze the behavior of readers, provide customized information resources recommendation services to readers, and meet the new diversified needs of readers. From the angle of wisdom recommendation, this paper probes into the intelligent service mode of university intelligent library, studies and designs the framework of intelligent service mode, and strengthens the adhesiveness of readers to university library. Some improvements and optimizations are put forward to the algorithm recommended by wisdom. The main work of this paper is as follows: (1) an empirical investigation on the wisdom recommendation service of 116 "211" colleges in China has been carried out, and the data obtained by means of website visits and questionnaires have been synthetically summarized and sorted out. Almost all colleges and universities provide some non-individualized service content, but the university library is still far from the intelligent library, the function of intelligent service is humanized, and the degree of intelligence is low. At the same time, it is too dependent on the simple recommendation function provided by OPAC system, and the recommendation service provided by the system is similar and simple. It designs the intelligent library service model of colleges and universities based on wisdom recommendation from four angles. It mainly includes the construction of intelligent retrieval service mode, intelligent recommendation service mode construction, intelligent APP service mode construction and intelligent micro-media service mode construction. 3) improve and optimize the traditional recommendation algorithm. According to the characteristics of the user group of readers in university library, this paper constructs the reader characteristic model, generates the candidate nearest neighbor set, generates the recommendation result, and makes the recommendation result more consistent with the reader's preference. In order to improve the accuracy of the recommendation results and make the readers rely on the wisdom recommendation service, this paper provides a certain algorithm support for the construction of the wisdom recommendation in the intelligence library of colleges and universities.
【学位授予单位】：天津理工大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：G258.6;G250.7

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