Please wait a minute...
Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (12): 43-51    DOI: 10.11925/infotech.2096-3467.2018.0419
Current Issue | Archive | Adv Search |
Building Interactive Knowledge Map for Academic Search
Liu Ping1,2(), Li Yanan1, Yu Cong1
1School of Information Management, Wuhan University, Wuhan 430072, China
2Institute for Digital Library, Wuhan University, Wuhan 430072, China
Download: PDF (3740 KB)   HTML ( 3
Export: BibTeX | EndNote (RIS)      

[Objective] This paper presents an approach to construct interactive knowledge map that facilitates browsing and keyword searching. [Methods] Firstly, we modeled academic resources to reveal the implicit knowledge nodes and their complex relationship. Then, we built the interactive knowledge map based on user queries, which suggested associated terms and presented results in lattice. [Results] We examined the proposed method with documents from Proceedings of the International ACM SIGIR Conference in recent 10 years. We discovered hidden knowledge structure helping users locate core concepts and improve searching. [Limitations] The recommendation of relevant concepts needs to be improved. [Conclusions] The proposed interactive knowledge map help users effectively explore the information space.

Key wordsAcademic Search      Knowledge Map      Interaction      Formal Concept Analysis     
Received: 16 April 2018      Published: 16 January 2019
ZTFLH:  G354  

Cite this article:

Liu Ping,Li Yanan,Yu Cong. Building Interactive Knowledge Map for Academic Search. Data Analysis and Knowledge Discovery, 2018, 2(12): 43-51.

URL:     OR

k1 k2 k3 k4 k5 k6
d1 X X X
d2 X X X X
d3 X X X
d4 X X X
d5 X X X
d6 X X
d7 X X X
d8 X X X
d9 X X
d10 X X X X
d11 X X X X
概念: {{外延}, {内涵}} 概念: {{外延}, {内涵}}
C1: {{d1, d2, d3, d4, d5, d6, d7, d8, d9, d10, d11}, {$\phi $}} C9: {{d1, d3, d5, d11}, {k1, k4}}
C2: {{d2, d4, d6, d8, d10}, {k2}} C10: {{d3, d9, d11}, {k1, k6}}
C3: {{d1, d2, d4, d5, d7, d8, d10, d11}, {k3}} C11: {{d2, d4, d8, d10}, {k2, k3, k4}}
C4: {{d1, d2, d3, d4, d5, d8, d10, d11}, {k4}} C12: {{d1, d5, d11}, {k1, k3, k4}}
C5: {{d1, d3, d5, d7, d9, d11}, {k1}} C13: {{d3, d11}, {k1, k4, k6}}
C6: {{d2, d6, d10}, {k2, k5}} C14: {{d2, d10}, {k2, k3, k4, k5}}
C7: {{d1, d2, d4, d5, d8, d10, d11}, {k3,k4}} C15: {{d11}, {k1, k3, k4, k6}}
C8: {{d1, d5, d7, d11}, {k1,k3}} C16: {{$\phi$}, {k1, k2, k3, k4, k5, k6}}
[1] Parolo P D B, Pan R K, Ghosh R, et al. Attention Decay in Science[J]. Journal of Informetrics, 2015, 9(4): 734-745.
doi: 10.1016/j.joi.2015.07.006
[2] 孟小峰, 慈祥. 大数据管理: 概念、技术与挑战[J]. 计算机研究与发展, 2013, 50(1): 146-169.
[2] (Meng Xiaofeng, Ci Xiang.Big Data Management: Concepts, Techniques and Challenges[J]. Journal of Computer Research & Development, 2013, 50(1): 146-169.)
[3] Yu J, Wu H, Tao C, et al.Acquisition and Representation of Knowledge for Academic Field[C]// Proceedings of the 2016 Asia-Pacific Web Conference. Springer, 2016: 289-297.
[4] 张进, 袁泽林, 陆伟. 信息检索可视化的主流路径[J]. 图书情报知识, 2008(5): 24-27.
[4] (Zhang Jin, Yuan Zelin, Lu Wei.Introduction to Mainstream Information Retrieval Visualization Approaches[J]. Documentation, Information & Knowledge, 2008(5): 24-27.)
[5] Kara S, Alan ö, Sabuncu O, et al.An Ontology-based Retrieval System Using Semantic Indexing[J]. Information Systems, 2012, 37(4): 294-305.
doi: 10.1016/
[6] Castells P, Fernández M, Vallet D.An Adaptation of the Vector-Space Model for Ontology-Based Information Retrieval[J]. IEEE Transactions on Knowledge & Data Engineering, 2007, 19(2): 261-272.
doi: 10.1109/TKDE.2007.22
[7] 周文. 基于概念的若干知识表示模型及相关方法研究[D]. 上海: 上海大学, 2007.
[7] (Zhou Wen.Several Concept-based Knowledge Representations and Related Approaches[D]. Shanghai: Shanghai University, 2007.)
[8] Qadi A E, Ghali B E, Aboutajddine D.Improving Information Retrieval by Query Expansion Using Formal Concept Analysis and Related Queries[A]// Artificial Intelligence and Hybrid Systems[M]. iConcept Press, 2013.
[9] Qadi A E, Aboutajedine D, Ennouary Y.Formal Concept Analysis for Information Retrieval[J]. International Journal of Computer Science & Information Security, 2010, 7(2): 119-125.
[10] Dunaiski M, Greene G J, Fischer B.Exploratory Search of Academic Publication and Citation Data Using Interactive Tag Cloud Visualizations[J]. Scientometrics, 2017, 110(3): 1539-1571.
doi: 10.1007/s11192-016-2236-3
[11] 滕广青, 崔林蔚. 大学图书馆网络用户柔性化细分[J]. 图书馆学研究, 2017(2): 44-51.
[11] (Teng Guangqing, Cui Linwei.Flexible Segmentation on Network Users of University Library[J]. Research on Library Science, 2017(2): 44-51.)
[12] Sun X, Chen Y, Li B, et al.Exploring Software Engineering Data with Formal Concept Analysis[C]// Proceedings of the 1st International Workshop on Data Analysis Patterns in Software Engineering. IEEE, 2013: 14-16.
[13] Orphanides C, Akhgar B, Bayerl P S.Discovering Knowledge in Online Drug Transactions Using Conceptual Graphs and Formal Concept Analysis[C]// Proceedings of the 7th Intelligence and Security Informatics Conference. IEEE, 2016: 100-103.
[14] Brookes B C.The Foundations of Information Science Part I. Philosophical Aspects[J]. Journal of Information Science, 1980, 2(3-4): 125-133.
doi: 10.1109/HICSS.1989.48136
[15] 王子舟, 王碧滢. 知识的基本组分——文献单元和知识单元[J]. 中国图书馆学报, 2003, 29(1): 5-11.
doi: 10.3969/j.issn.1001-8867.2003.01.001
[15] (Wang Zizhou, Wang Biying.The Basic Components of Knowledge ——Literature Unit and Knowledge Unit[J]. Journal of Library Science in China, 2003, 29(1): 5-11.)
doi: 10.3969/j.issn.1001-8867.2003.01.001
[16] 温有奎, 徐国华. 知识元链接理论[J]. 情报学报, 2003, 22(6): 665-670.
[16] (Wen Youkui, Xu Guohua.Knowledge Element Linking Theory[J]. Journal of the China Society for Scientific and Technical Information, 2003, 22(6): 665-670.)
[17] 温有奎, 徐端颐, 潘龙法. 基于XML平台的知识元本体推理[J]. 情报学报, 2004, 23(6):643-648.
doi: 10.3969/j.issn.1000-0135.2004.06.001
[17] (Wen Youkui, Xu Duanyi, Pan Longfa.Ontology Reasoning of Knowledge Element Based on XML Platform[J]. Journal of the China Society for Scientific and Technical Information, 2004, 23(6): 643-648.)
doi: 10.3969/j.issn.1000-0135.2004.06.001
[18] 文庭孝, 侯经川, 龚蛟腾, 等. 中文文本知识元的构建及其现实意义[J]. 中国图书馆学报, 2007, 33(6): 91-95.
doi: 10.3969/j.issn.1001-8867.2007.06.019
[18] (Wen Tingxiao, Hou Jingchuan, Gong Jiaoteng, et al.On the Construction of Chinese Text Knowledge Elements and Its Practical Significance[J]. Journal of Library Science in China, 2007, 33(6): 91-95.)
doi: 10.3969/j.issn.1001-8867.2007.06.019
[19] 贾茜, 张斌. 基于认知语言学的文献主题元语义表示与结构分析[J]. 情报理论与实践, 2015, 38(2): 6-10.
doi: 10.16353/j.cnki.1000-7490.2015.02.002
[19] (Jia Qian, Zhang Bin.Meta-semantic Representation and Structure Analysis of Literature Themes Based on Cognitive Linguistics[J]. Information Studies: Theory and Application, 2015, 38(2): 6-10.)
doi: 10.16353/j.cnki.1000-7490.2015.02.002
[20] 姜永常. 基于知识元语义链接的知识网络构建[J]. 情报理论与实践, 2011, 34(5): 50-53.
[20] (Jiang Yongchang.Knowledge Network Construction Based on Semantic Linking of Knowledge Element[J]. Information Studies: Theory and Application, 2011, 34(5): 50-53.)
[21] Lee J H, Segev A.Knowledge Maps for E-learning[J]. Computers & Education, 2012, 59(2): 353-364.
doi: 10.1016/j.compedu.2012.01.017
[22] Evans V.How Words Mean: Lexical Concepts, Cognitive Models, and Meaning Construction[M]. Oxford: Oxford University Press, 2009.
[23] Wille R.Restructing Lattice Theory: An Approach Based on Hierarchies of Concepts[C]// Proceedings of the 7th International Conference on Formal Concept Analysis. 2009: 314-339.
[24] Ganter B, Wille R.Formal Concept Analysis: Mathematical Foundations[M]. Springer, 1999.
[25] Poelmans J, Elzinga P, Dedene G.Retrieval of Criminal Trajectories with an FCA-based Approach[C]// Proceedings of the 2013 Formal Concept Analysis Meets Information Retrieval: Workshop Co-located with the 35th European Conference on Information Retrieval. 2013: 83-94.
[26] Ducrou J, Eklund P W.SearchSleuth: The Conceptual Neighbourhood of a Web Query[C]// Proceedings of the 5th International Conference on Concept Lattices and Their Applications. 2007, 331: 249-259.
[27] Nauer E, Toussaint Y.CreChainDo: An Iterative and Interactive Web Information Retrieval System Based on Lattices[J]. International Journal of General Systems, 2009, 38(4): 363-378.
doi: 10.1080/03081070902857613
[28] Carpineto C, Romano G.Exploiting the Potential of Concept Lattices for Information Retrieval with CREDO[J]. Journal of Universal Computer Science, 2004, 10(8): 985-1013.
[1] Hu Guangwei, Teng Jie, Liu Lu. Mining Topics of Social Appeals and Interprovincial Differences in Government-People Interaction——Case Study of E-mail Corpus of Provincial Leaders[J]. 数据分析与知识发现, 2021, 5(10): 15-27.
[2] Chen Shiji, Qiu Junping, Yu Bo. Topic Analysis of LIS Big Data Research with Overlay Mapping[J]. 数据分析与知识发现, 2021, 5(10): 51-59.
[3] Shao Qi,Mu Dongmei,Wang Ping,Jin Chunyan. Identifying Subjects of Online Opinion from Public Health Emergencies[J]. 数据分析与知识发现, 2020, 4(9): 68-80.
[4] Su Qing,Chen Sizhao,Wu Weimin,Li Xiaomei,Huang Tiankuan. Personalized Recommendation Model Based on Collaborative Filtering Algorithm of Learning Situation[J]. 数据分析与知识发现, 2020, 4(5): 105-117.
[5] Liu Ping,Peng Xiaofang. Calculating Word Similarities Based on Formal Concept Analysis[J]. 数据分析与知识发现, 2020, 4(5): 66-74.
[6] Jie Ma,Yan Ge,Hongyu Pu. Survey of Attribute Reduction Methods[J]. 数据分析与知识发现, 2020, 4(1): 40-50.
[7] Shengchun Ding,Linlin Hou,Ying Wang. Product Knowledge Map Construction Based on the E-commerce Data[J]. 数据分析与知识发现, 2019, 3(3): 45-56.
[8] Xiwei Wang,Duo Wang,Qingxiao Zheng,Ya’nan Wei. Information Interaction Between User and Enterprise in Online Brand Community: A Study of Virtual Reality Industry[J]. 数据分析与知识发现, 2019, 3(3): 83-94.
[9] Xiang Xue,Yuxiang Zhao. Exploring User Mental Models of Online Music Classification System: Case Study of College Students[J]. 数据分析与知识发现, 2019, 3(2): 1-12.
[10] Huiying Gao,Tian Wei,Jiawei Liu. Friend Recommendation Based on User Clustering and Dynamic Interaction Trust Relationship[J]. 数据分析与知识发现, 2019, 3(10): 66-77.
[11] Ma Yanyang,Liu Yulei,Xu Bochu,Zhi Jinyi. Impacts of Waiting on Mobile Users —— Case Study of Digital Novels[J]. 数据分析与知识发现, 2018, 2(8): 79-87.
[12] Zhang Liyi,Li Huiran. Studying Social Interaction of Online Medical Question-Answering Service[J]. 数据分析与知识发现, 2018, 2(1): 76-87.
[13] Wu Dan,Cheng Lei. Route Planning in Pedestrian-Map APP Interactions[J]. 数据分析与知识发现, 2017, 1(5): 12-22.
[14] Wu Dan,Yuan Fang. Studying User Distractions with GPS Based Pedestrian Navigation System[J]. 数据分析与知识发现, 2017, 1(5): 32-41.
[15] Ding Heng,Lu Wei. Building Standard Literature Knowledge Service System[J]. 现代图书情报技术, 2016, 32(7-8): 120-128.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938