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论文编号：	12356
作者编号：	2120183114
上传时间：	2021/6/9 12:19:20
中文题目：	基于用户需求的学术资源发现系统服务功能研究
英文题目：	Research on Service Function of Academic Resource Discovery System Based on User Demand
指导老师：	李颖
中文关键字：	系统功能研究;用户需求;学术资源发现系统
英文关键字：	system function research; user demand; academic resource discovery system
中文摘要：	目前，国内外已有很多图情机构引入了学术资源发现系统。这类系统大量且迅速地被采用证明了其对高校图书馆等机构的吸引力。然而，用户对于学术资源发现系统的使用程度却并未达到预期。当前针对学术资源发现系统进行的研究多从图书馆的视角进行考量，将重心放在元数据及系统架构上，对于与用户体验直接相关的功能研究重视不足。新环境下的学术资源发现系统不再简单地被视为学术搜索引擎，而需要更多地面向用户需求，体现其作为资源发现平台的价值。为实现其“发现”特性的逐步发展，系统需要引入那些在预发现时代无法实现的新功能。适应用户需求，丰富和完善系统功能，优化用户使用体验，是学术资源发现系统增强其用户群体黏性面临的挑战与机遇。因此，本文基于用户需求，对学术资源发现系统的服务功能进行了研究。 本文的主要研究目的是构建一个符合用户需求的学术资源发现系统服务功能层次模型，并且得到用户对学术资源发现系统各服务功能的重要性度量，从而为系统的服务功能优化提供指导。文章首先结合已有相关文献与用户访谈对学术资源发现系统用户的功能性需求进行了分析与提炼，并在归纳了用户典型使用模式的基础上对用户未意识到的潜在功能性需求进行了挖掘。再使用KJ分析法，将梳理汇总得到的56个用户功能性需求转化为22个系统服务功能要素；还进一步分析了各服务功能要素间的内在联系，对这些功能要素进行分类，将其划分为8个功能维度，构建出了初始的学术资源发现系统服务功能层次模型。在此基础上，结合KANO模型设计了调查问卷对用户进行调研，获知了用户对学术资源发现系统各服务功能要素的价值感知与需求程度，统计分析问卷数据从而得到了各功能要素的KANO属性，依据属性划分对功能要素进行筛选并确认了各功能要素的重要度及其优先级排序，构建出了整合重要度和优先级排序的最终学术资源发现系统服务功能层次模型。最后，使用该模型评价了超星发现和Primo两个学术资源发现系统的现有服务功能水平，针对系统功能存在的不足提出了优化的对策与建议，分别是检索与关联推荐功能的场景化、资源揭示的灵活化与深刻化以及资源获取与服务的一站式化。
英文摘要：	Nowadays, many library and information institutions have introduced the academic resource discovery system. The rapid adoption of academic resource discovery system proves its attraction to university libraries and other institutions. However, users' usage of the system is far less than expected. At present, the research on academic resource discovery system is mostly from the perspective of library, focusing on metadata and architecture, the research on function is insufficient. In the new environment, the academic resource discovery system is not only regarded as an academic search engine, it needs to be more oriented to user demands and reflect its value as a resource discovery platform. The system needs to introduce new functions that cannot be realized in the pre-discovery era. Adapting to the new demands of users, enriching and improving the service functions of the system, and optimizing the user experience are the challenges and opportunities faced by the academic resource discovery system to enhance the stickiness of the user. Therefore, this paper studies the service functions of the academic resource discovery system based on user demands. The main research purpose of this paper is to build a hierarchical model of the service function of academic resource discovery system that based on the demands of users, and obtain the user's importance measurement of the service functions, so as to provide guidance for the optimization of the system's service functions. This paper first analyzes the user's functional requirements of the academic resource discovery system in the existing literature and user interview data, puts forward the typical usage pattern of the academic resource discovery system, and on this basis, excavates the potential functional requirements that the users are not aware of. Then, using kJ analysis method, the 56 user demands are transformed into 22 system service function elements. Furthermore, this paper analyzes the internal relations among the service function elements of the system, classifies these functional elements into eight functional dimensions, and constructs the initial service function hierarchical model of the academic resource discovery system. After that, this paper design the questionnaire based on the KANO model, get the user’s value perception and demand for each service function element, and uses the questionnaire data to make statistics. The analysis result divides the KANO types of the service function elements. Based on the result of classification, two indistinguishable function were removed, and the final academic resource discovery system service function model was obtained. Then, through the semantic transformation of the questionnaire data, the user's evaluation of the importance of each service function element is obtained. Finally, based on the construction of the final academic resource discovery system service function model that integrates importance and priority ranking, this paper evaluates the level of existing service functions of two academic resource discovery systems, Chaoxing Discovery and Primo. In view of the current deficiencies of the system, this paper proposes the focus and direction of function optimization, which are the contextualization of retrieval and association recommendation, the flexibility and deepening of resource disclosure, and the one-stop resource acquisition and service.
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