Please wait a minute...
Data Analysis and Knowledge Discovery  2021, Vol. 5 Issue (5): 127-132    DOI: 10.11925/infotech.2096-3467.2020.0882
Current Issue | Archive | Adv Search |
Cross-database Knowledge Integration and Fingerprint of Institutional Repositories with Lingo3G Clustering Algorithm
Lu Linong1,2(),Zhu Zhongming1,Zhang Wangqiang1,Wang Xiaochun2
1Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
2CASWIZ Information Consulting Co., Ltd., Lanzhou 730000, China
Download: PDF (1037 KB)   HTML ( 12
Export: BibTeX | EndNote (RIS)      
Abstract  

[Objective] This study optimizes the Lingo3G algorithm with the help Solr scoring rules, aiming to realize the cross-database knowledge integration and knowledge fingerprint services of the institutional repository. [Methods] First, we analyzed user needs, and constructed a functional framework for knowledge integration analysis and visualization. Then, we selected key technologies and methods to build a platform, and explored the feasibility of knowledge integration. [Results] The proposed method calculated the characteristics of knowledge fingerprints in the institutional knowledge base. It organized and visualized knowledge fingerprints, as well as integrated cross-database knowledge through clustering. [Limitations] Due to the differences of database structure and cross-database retrieval methods ( i.e., no public resource API), we did not address all limits of cross-database retrieval. [Conclusions] The proposed method could help institutional knowledge repositories effectively integrate their knowledge resources and improve service capabilities.

Key wordsInstitutional      Repository      Clustering      Algorithm      Knowledge      Integration      Knowledge      FingerprintCross-library      Retrieval      Lingo3G     
Received: 07 September 2020      Published: 27 May 2021
ZTFLH:  G354  
Corresponding Authors: Lu Linong     E-mail: luln@llas.ac.cn

Cite this article:

Lu Linong,Zhu Zhongming,Zhang Wangqiang,Wang Xiaochun. Cross-database Knowledge Integration and Fingerprint of Institutional Repositories with Lingo3G Clustering Algorithm. Data Analysis and Knowledge Discovery, 2021, 5(5): 127-132.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2020.0882     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2021/V5/I5/127

Knowledge Integration and Knowledge Fingerprint Framework
Clustering Algorithm Code
Ling3G Clustering Algorithm Process
Knowledge Service Scenario Configuration
Knowledge Topic Tree Distribution
Knowledge Fingerprint Distribution
[1] 侯莉. 知识管理在图书档案管理中的功能及应用[J]. 兰台内外, 2020(23):10-12.
[1] ( Hou Li. The Function and Application of Knowledge Management in the Management of Books and Archives[J]. Inside and Outside Lantai, 2020(23):10-12.)
[2] 席亚军. 高校图书馆数字资源建设现状及发展趋势研究[J]. 河南图书馆学刊, 2016,36(2):41-43.
[2] ( Xi Yajun. Research on the Status Quo and Development Trend of Digital Resources Construction in Academic Libraries[J]. The Library Journal of Henan, 2016,36(2):41-43.)
[3] 韦卫. 图书馆跨库检索背景下的资源整合与优化[J]. 图书馆学刊, 2019,41(12):86-89, 98.
[3] ( Wei Wei. Resource Integration and Optimization in the Context of Library Cross-database Retrieval[J]. Journal of Library Science, 2019,41(12):86-89, 98.)
[4] 南晓凡. 基于跨库检索的数字图书馆资源整合方式研究[J]. 图书馆学刊, 2016,38(1):116-118.
[4] ( Nan Xiaofan . Research on the Integration of Digital Library Resources Based on Cross-database Retrieval[J]. Journal of Library Science, 2016,38(1):116-118.)
[5] 张浩洋, 周良. 改进的GHSOM算法在民航航空法规知识地图构建中的应用[J]. 计算机科学, 2020,47(S1):429-435.
[5] ( Zhang Haoyang, Zhou Liang. The Application of Improved GHSOM Algorithm in the Construction of Civil Aviation Regulations Knowledge Map[J]. Computer Science, 2020,47(S1):429-435.)
[6] Lingo3G[EB/OL]. [ 2020- 08- 25]. http://get.carrotsearch.com/lingo3g/manual/ .
[7] 吴志强, 祝忠明, 刘巍, 等. CSpace知识分析与可视化功能扩展研究与实践[J]. 数据分析与知识发现, 2019,3(3):112-119.
[7] ( Wu Zhiqiang, Zhu Zhongming, Liu Wei, et al. Research and Practice on the Extension of Knowledge Analysis and Visualization Function in CSpace[J]. Data Analysis and Knowledge Discovery, 2019,3(3):112-119.)
[8] 王睿, 陈抒, 曾斌. 图书馆信息资源跨库检索技术研究[J]. 情报探索, 2017(10):56-61.
[8] ( Wang Rui, Chen Shu, Zeng Bin. Cross-database Search Technology for Library Information Resource[J]. Information Research, 2017(10):56-61.)
[9] 王洪军, 张玉, 李焱, 等. 基于Web的中文期刊查收查引跨库检索系统研发[J]. 中华医学图书情报杂志, 2016,25(6):24-28.
[9] ( Wang Hongjun, Zhang Yu, Li Yan, et al. Web-based R&D of Cross-database Retrieval System for Papers and Citations Covered in Chinese Journals[J]. Chinese Journal of Medical Library and Information Science, 2016,25(6):24-28.)
[10] 胡诗未, 李晓峰, 徐伟. 基于主题词匹配频数的搜索引擎结果聚类算法[J]. 计算机工程与科学, 2011,33(6):130-132.
[10] ( Hu Shiwei, Li Xiaofeng, Xu Wei. An Algorithm for the Search Results Clustering Based on Topic Words Matching Frequency[J]. Computer Engineering and Science, 2011,33(6):130-132.)
[11] 李亚, 邵引平. 基于LabWindows/CVI的远程接口单元测试系统软件设计[J]. 计算机测量与控制, 2020,28(7):148-152, 157.
[11] ( Li Ya, Shao Yinping. Design of Remote Interface Unit Testing System Software Based on LabWindows/CVI[J]. Computer Measurement and Control, 2020,28(7):148-152, 157.)
[12] 王海东, 陈广山. 机构自建知识库模式研究及其学术资源整合策略[J]. 福建电脑, 2015,31(6):69-70, 85.
[12] ( Wang Haidong, Chen Guangshan. Research on the Self-built Knowledge Base Model and its Academic Resource Integration Strategy[J]. Fujian Computer, 2015,31(6):69-70, 85.)
[1] Shan Xiaohong,Wang Chunwen,Liu Xiaoyan,Han Shengxi,Yang Juan. Identifying Lead Users in Open Innovation Community from Knowledge-based Perspectives[J]. 数据分析与知识发现, 2021, 5(9): 85-96.
[2] Li Wenna,Zhang Zhixiong. Research on Knowledge Base Error Detection Method Based on Confidence Learning[J]. 数据分析与知识发现, 2021, 5(9): 1-9.
[3] Lu Yunmeng,Liu Tiezhong. Diffusion Model for Tacit Knowledge of Scientific Cooperation Network Based on Relevance: Case Study of Major Sci-Tech Projects[J]. 数据分析与知识发现, 2021, 5(9): 10-20.
[4] Zhou Yang,Li Xuejun,Wang Donglei,Chen Fang,Peng Lijuan. Visualizing Knowledge Graph for Explosive Formula Design[J]. 数据分析与知识发现, 2021, 5(9): 42-53.
[5] Wang Ruolin, Niu Zhendong, Lin Qika, Zhu Yifan, Qiu Ping, Lu Hao, Liu Donglei. Disambiguating Author Names with Embedding Heterogeneous Information and Attentive RNN Clustering Parameters[J]. 数据分析与知识发现, 2021, 5(8): 13-24.
[6] Chai Qingfeng, Shi Linyan, Mei Shan, Xiong Haitao, He Huixin. Extracting Knowledge Elements of Sci-Tech Literature Based on Artificial and Machine Features[J]. 数据分析与知识发现, 2021, 5(8): 132-144.
[7] Su Qiang, Hou Xiaoli, Zou Ni. Predicting Surgical Infections Based on Machine Learning[J]. 数据分析与知识发现, 2021, 5(8): 65-75.
[8] Shen Kejie, Huang Huanting, Hua Bolin. Constructing Knowledge Graph with Public Resumes[J]. 数据分析与知识发现, 2021, 5(7): 81-90.
[9] Dong Mei,Chang Zhijun,Zhang Runjie. A Multiple Pattern Matching Algorithm for Specifications of Incremental Metadata for Sci-Tech Literature[J]. 数据分析与知识发现, 2021, 5(6): 135-144.
[10] Huang Mingxuan,Jiang Caoqing,Lu Shoudong. Expanding Queries Based on Word Embedding and Expansion Terms[J]. 数据分析与知识发现, 2021, 5(6): 115-125.
[11] Dong Zhenheng,Lv Xueqiang,Ren Weiping,Jiang Yang,Li Guolin. Review of Key Technologies of High Performance Blockchain[J]. 数据分析与知识发现, 2021, 5(6): 14-24.
[12] Wang Xiwei,Jia Ruonan,Wei Yanan,Zhang Liu. Clustering User Groups of Public Opinion Events from Multi-dimensional Social Network[J]. 数据分析与知识发现, 2021, 5(6): 25-35.
[13] Ruan Xiaoyun,Liao Jianbin,Li Xiang,Yang Yang,Li Daifeng. Interpretable Recommendation of Reinforcement Learning Based on Talent Knowledge Graph Reasoning[J]. 数据分析与知识发现, 2021, 5(6): 36-50.
[14] Ma Yingxue,Gan Mingxin,Xiao Kejun. A Matrix Factorization Recommendation Method with Tags and Contents[J]. 数据分析与知识发现, 2021, 5(5): 71-82.
[15] Meng Zhen,Wang Hao,Yu Wei,Deng Sanhong,Zhang Baolong. Vocal Music Classification Based on Multi-category Feature Fusion[J]. 数据分析与知识发现, 2021, 5(5): 59-70.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn