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数据分析与知识发现  2018, Vol. 2 Issue (12): 43-51     https://doi.org/10.11925/infotech.2096-3467.2018.0419
  研究论文 本期目录 | 过刊浏览 | 高级检索 |
面向学术搜索的交互式知识地图建构研究*
刘萍1,2(), 李亚楠1, 郁聪1
1武汉大学信息管理学院 武汉 430072
2武汉大学数字图书馆研究所 武汉 430072
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
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摘要 

【目的】针对传统学术搜索中分类浏览和关键词搜索分离的局限性, 提出一种融合浏览和搜索的交互式知识地图建构方法。【方法】对学术资源进行数学建模, 挖掘出文献集合隐含的知识节点及复杂关联关系。在此 基础上构建基于用户查询的交互式知识地图, 展示核心关联词汇并以概念格的形式展现检索结果。【结果】以2006年-2016年国际SIGIR会议收录的学术文献为例进行应用分析, 结果表明利用本文方法能揭示文档空间隐含的知识结构, 帮助用户快速聚焦核心知识节点、提高搜索效率。【局限】在概念的智能推荐方面还有待提高。【结论】所构建的交互式知识地图能满足用户对信息空间认知和探索的需求。

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刘萍
李亚楠
郁聪
关键词 学术搜索知识地图交互形式概念分析    
Abstract

[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
收稿日期: 2018-04-16      出版日期: 2019-01-16
ZTFLH:  G354  
基金资助:*本文系国家自然科学基金项目“基于个性化知识地图的交互式信息检索系统研究——从用户认知的角度”(项目编号: 71573196)的研究成果之一
引用本文:   
刘萍, 李亚楠, 郁聪. 面向学术搜索的交互式知识地图建构研究*[J]. 数据分析与知识发现, 2018, 2(12): 43-51.
Liu Ping,Li Yanan,Yu Cong. Building Interactive Knowledge Map for Academic Search. Data Analysis and Knowledge Discovery, 2018, 2(12): 43-51.
链接本文:  
https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.2096-3467.2018.0419      或      https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2018/V2/I12/43
  文档空间隐含概念挖掘和关联模型
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
  信息空间形式背景
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}}
  从表1形式背景中提取的概念
  表1形式背景中隐含的概念及其关系
  基于查询词k4的局部知识地图
  以C7为核心的局部知识地图
  部分文档空间形式背景
  局部知识地图1
  局部知识地图2
  局部知识地图3
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