ARCA。书店的语义探索

Eleonora Bernasconi, Miguel Ceriani, Massimo Mecella, T. Catarci, M. C. Capanna, Clara di Fazio, R. Marcucci, Erik Pender, Fabio Maria Petriccione
{"title":"ARCA。书店的语义探索","authors":"Eleonora Bernasconi, Miguel Ceriani, Massimo Mecella, T. Catarci, M. C. Capanna, Clara di Fazio, R. Marcucci, Erik Pender, Fabio Maria Petriccione","doi":"10.1145/3399715.3399939","DOIUrl":null,"url":null,"abstract":"In this demo paper, we present ARCA, a visual-search based system that allows the semantic exploration of a bookstore. Navigating a domain-specific knowledge graph, students and researchers alike can start from any specific concept and reach any other related concept, discovering associated books and information. To achieve this paradigm of interaction we built a prototype system, flexible and adaptable to multiple contexts of use, that extracts semantic information from the contents of a books' corpus, building a dedicated knowledge graph that is linked to external knowledge bases. The web-based user interface of ARCA integrates text-based search, visual knowledge graph navigation, and linear visualization of filtered books (ordered according to multiple criteria) in a comprehensive coordinated view aimed at exploiting the underlying data while avoiding information overload and unnecessary cluttering. A proof-of-concept of ARCA is available online at http://arca.diag.uniroma1.it","PeriodicalId":149902,"journal":{"name":"Proceedings of the International Conference on Advanced Visual Interfaces","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"ARCA. Semantic exploration of a bookstore\",\"authors\":\"Eleonora Bernasconi, Miguel Ceriani, Massimo Mecella, T. Catarci, M. C. Capanna, Clara di Fazio, R. Marcucci, Erik Pender, Fabio Maria Petriccione\",\"doi\":\"10.1145/3399715.3399939\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this demo paper, we present ARCA, a visual-search based system that allows the semantic exploration of a bookstore. Navigating a domain-specific knowledge graph, students and researchers alike can start from any specific concept and reach any other related concept, discovering associated books and information. To achieve this paradigm of interaction we built a prototype system, flexible and adaptable to multiple contexts of use, that extracts semantic information from the contents of a books' corpus, building a dedicated knowledge graph that is linked to external knowledge bases. The web-based user interface of ARCA integrates text-based search, visual knowledge graph navigation, and linear visualization of filtered books (ordered according to multiple criteria) in a comprehensive coordinated view aimed at exploiting the underlying data while avoiding information overload and unnecessary cluttering. A proof-of-concept of ARCA is available online at http://arca.diag.uniroma1.it\",\"PeriodicalId\":149902,\"journal\":{\"name\":\"Proceedings of the International Conference on Advanced Visual Interfaces\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the International Conference on Advanced Visual Interfaces\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3399715.3399939\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Conference on Advanced Visual Interfaces","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3399715.3399939","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

在这篇演示论文中,我们介绍了ARCA,一个基于视觉搜索的系统,它允许对书店进行语义探索。通过浏览特定领域的知识图谱,学生和研究人员都可以从任何特定的概念开始,到达任何其他相关的概念,发现相关的书籍和信息。为了实现这种交互范例,我们构建了一个原型系统,灵活且可适应多种使用上下文,从图书语料库的内容中提取语义信息,构建一个与外部知识库链接的专用知识图。ARCA的基于web的用户界面将基于文本的搜索、视觉知识图导航和过滤图书的线性可视化(根据多个标准排序)集成在一个全面协调的视图中,旨在利用底层数据,同时避免信息过载和不必要的混乱。ARCA的概念验证可在http://arca.diag.uniroma1.it网站上获得
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
ARCA. Semantic exploration of a bookstore
In this demo paper, we present ARCA, a visual-search based system that allows the semantic exploration of a bookstore. Navigating a domain-specific knowledge graph, students and researchers alike can start from any specific concept and reach any other related concept, discovering associated books and information. To achieve this paradigm of interaction we built a prototype system, flexible and adaptable to multiple contexts of use, that extracts semantic information from the contents of a books' corpus, building a dedicated knowledge graph that is linked to external knowledge bases. The web-based user interface of ARCA integrates text-based search, visual knowledge graph navigation, and linear visualization of filtered books (ordered according to multiple criteria) in a comprehensive coordinated view aimed at exploiting the underlying data while avoiding information overload and unnecessary cluttering. A proof-of-concept of ARCA is available online at http://arca.diag.uniroma1.it
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
HeyTAP Comparing and Exploring High-Dimensional Data with Dimensionality Reduction Algorithms and Matrix Visualizations VITRuM Evaluating User Preferences for Augmented Reality Interactions with the Internet of Things TieLent
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1