用户画像视角下自助图书馆个性化推荐服务研究
摘要
随着云计算技术的不断发展，各行业的服务模式愈加多样化，以用户体验为
核心的互动式服务成为现阶段研究的热点之一。而用户画像作为一种抽象用户信
息、刻画用户形象、突出用户特征的工具，被广泛应用于个性化推荐服务中，也
为自助图书馆服务创新发展变革注入新活力。自助图书馆构建用户画像模型，以
用户数据为参考，深入了解用户兴趣偏好，为实现自助图书馆资源与用户需求的
双向匹配提供新参考。
本文将用户画像引入自助图书馆服务领域，采用定性和定量相结合的分析方
法，遵循从理论研究到模型构建再到实证研究的流程，主要从以下几个方面展开
研究：首先，介绍研究背景和意义，梳理用户画像、自助图书馆服务的国内外研
究现状，阐述用户画像、自助图书馆服务等相关概念，为自助图书馆的用户画像
模型构建和实证分析提供理论依据。其次，将自助图书馆和用户画像相结合，提
出自助图书馆用户画像的必需性，进而阐述了用户画像在自助图书馆个性化推荐
服务中的功能，包括整合用户数据、定位目标用户和辅助个性化推荐服务，作为
自助图书馆用户画像模型构建的基础。再次，在引入用户画像的基础上，介绍画
像模型架构，阐述自助图书馆用户画像标签体系设计和权重设置，利用 K-means
算法对自助图书馆用户进行聚类分析，进而提出用户偏好相似与偏好互补相结合
的推荐服务方案，并采用问卷调查的方法分析用户对该方案的满意程度，最后总
结性提出自助图书馆个性化推荐服务优化策略，以期实现自助图书馆个性化推荐
服务创新。
关键词：自助图书馆用户画像K-means 算法个性化推荐服务
RESEARCH ON PERSONALIZED RECOMMENDATION
SERVICE OF SELF-SERVICE LIBRARY FROM THE
PERSPECTIVE OF USER PROFILE
ABSTRACT
With the continuous development of cloud computing technology, the service
modes of various industries are becoming more and more diverse, and interactive
services centered on user experience have become one of the hotspots of research at
this stage. As a tool to abstract user information, describe user image, and highlight
user characteristics,user profile iswidely used in personalizedrecommendation
services, and it also injects new vitalityinto the innovation and development of
self-service library services. The self-service library builds a user profile model, takes
user data as a reference, and deeply understands users' interests and preferences,
providing new references for the realization of two-way matching between self-service
library resources and user needs.
This paper introduces user profiles into the field of self-service library services,
adopts a combination of qualitative and quantitative analysis methods, and follows the
process from theoretical foundation to model construction to empirical research. The
significance of this paperis to sort out the researchstatus of user profiles and
self-service library services at home and abroad, and expounds related concepts such
as user profiles and self-service library services. Secondly, combining the self-service
library with user profiles, the necessity of user profiles in self-service libraries is
proposed, and then the functions of user profiles in the personalized recommendation
service of self-service libraries are expounded, including integrating user data, locating
target users and assistingpersonality. It provides a personalized recommendation
service as the basis for the construction of the user profile model of the self-service
library. Thirdly, based on the introduction of user profile, this paper introduces the
profile model architecture, expounds the design and weight setting of the user profile
label system in the self-service library, uses the K-means algorithm to perform cluster
analysis on the users of the self-service library, and then proposes the similarity and
preference of users. This paper analyzes the user's satisfaction with the scheme by
means of a questionnaire survey, and finally puts forward the optimization strategy of
the personalized recommendation service of the self-service library, in order to realize
the innovation of the personalized recommendation service of the self-service library.
KEY WORDS: self-service libraryuser profileK-means algorithmpersonalized
recommendation service