CKGSE: A Prototype Search Engine for Chinese Knowledge Graphs

Author:

Wang Xiaxia1,Lin Tengteng1,Luo Weiqing1,Cheng Gong1,Qu Yuzhong1

Affiliation:

1. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China

Abstract

Abstract Nowadays, with increasing open knowledge graphs (KGs) being published on the Web, users depend on open data portals and search engines to find KGs. However, existing systems provide search services and present results with only metadata while ignoring the contents of KGs, i.e., triples. It brings difficulty for users' comprehension and relevance judgement. To overcome the limitation of metadata, in this paper we propose a content-based search engine for open KGs named CKGSE. Our system provides keyword search, KG snippet generation, KG profiling and browsing, all based on KGs' detailed, informative contents rather than their brief, limited metadata. To evaluate its usability, we implement a prototype with Chinese KGs crawled from OpenKG.CN and report some preliminary results and findings.

Publisher

MIT Press - Journals

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference39 articles.

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. ACORDAR 2.0: A Test Collection for Ad Hoc Dataset Retrieval with Densely Pooled Datasets and Question-Style Queries;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

2. Enhancing Dataset Search with Compact Data Snippets;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

3. A Knowledge Graph Embedding Model Based on Cyclic Consistency—Cyclic_CKGE;Applied Sciences;2023-11-16

4. Dense Re-Ranking with Weak Supervision for RDF Dataset Search;The Semantic Web – ISWC 2023;2023

5. ACORDAR;Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval;2022-07-06

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3