基于三元交互决定论的在线学术社区动态知识推荐服务模型研究

doi:10.13998/j.cnki.issn1002-1248.20-1054

摘要/Abstract

摘要： [目的/意义]以三元交互决定论为基石构建在线学术社区动态知识推荐服务模型,为在线社区多维需求分析及需求演变趋势刻画提供理论依据,为完善知识社区的推荐服务提供相应指导。[方法/过程]首先,基于三元交互决定论明确影响用户知识需求的内外因素以及因素间的关联关系;然后根据三元交互决定论需求分析的目标,明确相应的分析方法,抽取出用户各维度的知识需求特征;最后对各维度的需求特征进行整合并构建知识需求链以刻画三要素交互作用下的用户需求演变轨迹,利用需求链的相似度计算预测用户的将来知识需求,对用户的知识需求分析进行扩充;[结果/结论]基于三元交互决定论的知识推荐服务体系,从全局视角充分考虑了用户需求的各项影响因素,提高了社区对用户需求刻画的细粒度,对学术社区知识服务水平的提高具有重要的参考价值。

关键词: 在线学术社区, 三元交互决定论, 动态知识推荐服务, 知识服务

Abstract: [Purpose/Significance] This paper constructs a dynamic knowledge recommendation service model oriented to online academic communities based on ternary interactive determinism to provide a theoretical basis for online community multi-dimensional demand analysis and demand evolution trend description, to improve the knowledge community recommendation services. [Method/Process] Firstly, based on the ternary interactive determinism, we clarify the internal and external factors that affect the user's knowledge needs and analyze the relationship between the factors. Secondly, according to the needs analysis objective of the ternary interactive determinism, we clarify the corresponding analysis methods and extract the characteristics of users' knowledge needs in various dimensions. Finally, we integrate the demand characteristics of various dimensions and build a knowledge demand chain to describe the evolution of user demand under the interaction of the three elements. We use the similarity of the demand chain to calculate and predict the future knowledge demand of users to expand the analysis of users' knowledge demand. [Results/Conclusions] The knowledge recommendation service system based on the ternary interactive determinism fully considers the various influencing factors of user needs from a global perspective, improves the fine-grained characterization of user needs in the community, and provides reference for academic communities to improve their knowledge service levels.

Key words: online academic community, ternary interactive determinism, dynamic knowledge recommendation service, knowledge service

中图分类号:

赵雪芹, 王青青, 蔡铨. 基于三元交互决定论的在线学术社区动态知识推荐服务模型研究[J]. 农业图书情报学报, 2021, 33(5): 4-13.

ZHAO Xueqin, WANG Qingqing, CAI Quan. Dynamic Knowledge Recommendation Service Model of Online Academic Community Based on Ternary Interactive Determinism[J]. Journal of Library and Information Science in Agriculture, 2021, 33(5): 4-13.

参考文献

[1] 秦川, 祝恒书, 庄福振, 等. 基于知识图谱的推荐系统研究综述[J]. 中国科学: 信息科学, 2020, 50(7): 937-956.
QIN C, ZHU H S, ZHUANG F Z, et al.Review of recommender system based on knowledge map[J]. Chinese science: Information science, 2020, 50(7): 937-956.
[2] 李泽中, 张海涛, 张鑫蕊, 等. 融合用户社交与情境信息的虚拟知识社区个性化知识推荐研究[J]. 情报理论与实践, 2020, 43(4):152-158.
LI Z Z, ZHANG H T, ZHANG X R, et al.Research on personalized knowledge recommendation of virtual knowledge community integrating user social and situational information[J]. Intelligence theory and practice, 2020, 43(4): 152-158.
[3] 李秉祥, 袁烨. 经理管理防御对企业融资行为影响路径研究——基于三元交互分析框架[J]. 现代财经(天津财经大学学报), 2016, 36(5): 102-113.
LI B X, YUAN Y.Research on the influence path of manager man-agement defense on enterprise financing behavior based on ternary interaction analysis framework[J]. Modern finance and economics (Journal of Tianjin university of finance and economics), 2016, 36(5): 102-113.
[4] 吴遐, 高记, 刘兵. 以评促学:基于三元交互决定论的同伴互评研究[J]. 中国远程教育, 2020, 41(4) :58-64, 77.
WU X, GAO J, LIU B.Promoting learning by evaluation: a study of peer evaluation based on ternary interactive determinism[J]. Chinadistance education, 2020, 41(4): 58-64, 77.
[5] 黄河, 李经天. 班杜拉三元交互决定论对初中生问题行为矫正的启示[J]. 太原师范学院学报(社会科学版), 2017, 16(6): 119-121.
HUANG H, LI J T.The enlightenment of bandura's ternary interactive determinism on the problem behavior correction of junior high school students[J]. Journal of Taiyuan normal university (social science edition), 2017, 16(6): 119-121.
[6] 刘亮. 学前教育专业学生语文素养现状与提升策略研究——基于三元交互决定论[J]. 岳阳职业技术学院学报, 2016, 31(2): 30-33.
LIU LANG.Research on the current situation and promotion strate-gies of Chinese literacy of preschool education majors-Based on ternary interactive determinism[J]. Journal of Yueyang vocational and technical college, 2016, 31(2): 30-33.
[7] 王雅倩, 曹高辉, 曹星月. 农村留守儿童课外阅读行为影响因素研究[J]. 图书馆论坛, 2020, 40(10): 116-126.
WANG Y Q, CAO G H, CAO X Y.Study on influencing factors of rural left behind children's extracurricular reading behavior[J].Library forum, 2020, 40(10): 116-126.
[8] 马捷, 贾荟珍. 自我效能视角下阅读推广三元交互模型构建[J]. 图书与情报, 2019(2): 46-56.
MA J, JIA H Z.The construction of the three-dimensional interactive model of reading promotion from the perspective of self-efficacy[J]. Books and information, 2019(2): 46-56.
[9] 杜昊. 基于三元交互决定论的大学生阅读素养研究[J]. 图书馆工作与研究, 2019(1): 14-18.
DU H.Research on college students' reading literacy based on ternary interactive determinism[J]. Library work and research, 2019(1): 14-18.
[10] 朱代琼, 王国华. 突发事件中网民社会情绪产生的影响因素及机理——基于三元交互决定论的多个案定性比较分析(QCA)[J]. 情报杂志, 2020, 39(3): 95-104.
ZHU D Q, WANG G H.Influencing factors and mechanism of netizens' social emotions in emergencies: a qualitative comparative analysis of multiple cases based on ternary interactive determinism[J]. Journal of information, 2020, 39(3): 95-104.
[11] 房小可, 叶莎莎, 严承希. 融合情境语义的虚拟学术社区知识推荐模型研究[J]. 情报理论与实践, 2019, 42(9): 154-159.
FANG X K, YE S S, YAN C X.Research on knowledge recom-mendation model of virtual academic community integrating situa-tional semantics[J]. Intelligence theory and practice, 2019, 42(9):154-159.
[12] 游凤霞. 高校图书馆读者个性化服务系统的设计[J]. 农业图书情报学刊, 2018, 30(12): 112-115.
YOU F X.Design of reader personalized service system in university library[J]. Journal of agricultural library and information science, 2018, 30(12): 112-115.
[13] 李春英, 汤庸, 陈国华, 等. 面向学术社区的专家推荐模型[J]. 智能系统学报, 2012, 7(4): 365-369.
LI C Y, TTANG Y, CHEN G H, et al.Expert recommendation mod-el for academic community[J]. Journal of intelligent systems, 2012,7(4): 365-369.
[14] JORDAN K.Academics and their online networks: Exploring the role of academic social networking sites[J]. First Monday, 2014, 19(11).
[15] 张继东, 蔡雪. 基于社区划分和用户相似度的好友信息服务推荐研究[J]. 情报理论与实践, 2019, 42(4): 151-157, 165.
ZHANG J D, CAI X.Recommendation of friends information ser-vice based on community division and user similarity[J]. Intelli-gence theory and practice, 2019, 42(4): 151-157, 165.
[16] 杨丰瑞, 郑云俊, 张昌. 结合非负矩阵分解的主题社区好友推荐算法[J]. 计算机应用研究, 2018, 35(12): 3624-3627.
YANG F R, ZHENG Y J, ZHANG C.Friend recommendation algorithm based on non-negative matrix factorization in theme community[J]. Computer application research, 2018, 35(12): 3624-3627.
[17] 程秀峰, 周玮琩, 张小龙. 面向图书馆智慧服务的情境感知技术研究综述[J]. 农业图书情报学报, 2020, 32(5): 4-12.
CHENG X F, ZHOU W F, ZHANG X L.Research review on con-text awareness technology for library intelligent service[J]. Journalof agricultural library and information science, 2020, 32(5): 4-12.
[18] 余以胜, 陈咏晖. 基于用户属性—关系相似度的好友推荐模型研究[J]. 情报理论与实践, 2020, 43(2): 137-142, 163.
YU Y S, CHEN Y H.Research on friend recommendation model based on user attribute relationship similarity[J]. Intelligence theory and practice, 2020, 43(2): 137-142, 163.
[19] 张莉曼, 张向先, 吴雅威, 等. 基于小数据的社交类学术app用户动态画像模型构建研究[J]. 图书情报工作, 2020, 64(5): 50-59.
ZHANG L M, ZHANG X X, WU Y W, et al.Research on the construction of user dynamic portrait model of social academic app based on small data[J]. Library and information work, 2020, 64(5): 50-59.