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2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)最新文献

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Message from the Program Committee Chairs 来自计划委员会主席的信息
2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL) Pub Date : 2021-09-01 DOI: 10.1109/jcdl52503.2021.00006
{"title":"Message from the Program Committee Chairs","authors":"","doi":"10.1109/jcdl52503.2021.00006","DOIUrl":"https://doi.org/10.1109/jcdl52503.2021.00006","url":null,"abstract":"","PeriodicalId":112400,"journal":{"name":"2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)","volume":"56 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133753434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Assisted Text Annotation Using Active Learning to Achieve High Quality with Little Effort 使用主动学习辅助文本注释，以较少的努力实现高质量
2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL) Pub Date : 2021-09-01 DOI: 10.1109/JCDL52503.2021.00038
Franziska Weeber, Felix Hamborg, K. Donnay, Bela Gipp
{"title":"Assisted Text Annotation Using Active Learning to Achieve High Quality with Little Effort","authors":"Franziska Weeber, Felix Hamborg, K. Donnay, Bela Gipp","doi":"10.1109/JCDL52503.2021.00038","DOIUrl":"https://doi.org/10.1109/JCDL52503.2021.00038","url":null,"abstract":"Large amounts of annotated data have become more important than ever, especially since the rise of deep learning techniques. However, manual annotations are costly. We propose a tool that enables researchers to create large, high-quality, annotated datasets with only a few manual annotations, thus strongly reducing annotation cost and effort. For this purpose, we combine an active learning (AL) approach with a pre-trained language model to semi-automatically identify annotation categories in the given text documents. To highlight our research direction's potential, we evaluate the approach on the task of identifying frames in news articles. Our preliminary results show that employing AL strongly reduces the number of annotations for correct classification of even these complex and subtle frames. On the framing dataset, the AL approach needs only 16.3% of the annotations to reach the same performance as a model trained on the full dataset.","PeriodicalId":112400,"journal":{"name":"2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134180490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Proceedings 2021 ACM/IEEE Joint Conference on Digital Libraries [Front cover] 2021 ACM/IEEE数字图书馆联合会议论文集[封面]
2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL) Pub Date : 2021-09-01 DOI: 10.1109/jcdl52503.2021.00002
{"title":"Proceedings 2021 ACM/IEEE Joint Conference on Digital Libraries [Front cover]","authors":"","doi":"10.1109/jcdl52503.2021.00002","DOIUrl":"https://doi.org/10.1109/jcdl52503.2021.00002","url":null,"abstract":"","PeriodicalId":112400,"journal":{"name":"2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134061621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
DSDB: An Open-Source System for Database Versioning & Curation DSDB:一个开源的数据库版本管理系统
2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL) Pub Date : 2021-09-01 DOI: 10.1109/JCDL52503.2021.00044
Eva Maxfield Brown, Nicholas M. Weber
{"title":"DSDB: An Open-Source System for Database Versioning & Curation","authors":"Eva Maxfield Brown, Nicholas M. Weber","doi":"10.1109/JCDL52503.2021.00044","DOIUrl":"https://doi.org/10.1109/JCDL52503.2021.00044","url":null,"abstract":"In the following poster we describe the design and evaluation of DatasetDatabase (DSDB), an open-source system for handling the provenance, versioning, de-duplication, history, and query of dynamic databases in order to enable verifiable and shareable results - features necessary for fully reproducible computational modeling research. We present empirical work that motivates an initial design and deployment of DSDB, evaluate the results of this work for computational modeling at the Allen Institute for Cell Science, and conclude with a discussion of the future work necessary for provisioning data discovery and sharing tools that facilitate transparent reproducible research through provenance aware features.","PeriodicalId":112400,"journal":{"name":"2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122660694","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Resource Types linked in Academic Reading Lists 在学术阅读列表中链接的资源类型
2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL) Pub Date : 2021-09-01 DOI: 10.1109/JCDL52503.2021.00080
Ppnv Kumara, A. Hinze, Nicholas Vanderschantz, Claire Timpany, Sarah-Jane Saravani
{"title":"Resource Types linked in Academic Reading Lists","authors":"Ppnv Kumara, A. Hinze, Nicholas Vanderschantz, Claire Timpany, Sarah-Jane Saravani","doi":"10.1109/JCDL52503.2021.00080","DOIUrl":"https://doi.org/10.1109/JCDL52503.2021.00080","url":null,"abstract":"Reading List Systems are widely used in tertiary education as a pedagogical tool and for tracking use of copyrighted material. This paper explores the types of resources that are linked in reading lists, in particular the inclusion of electronic materials. A mixed-methods approach was employed in which we first performed a transaction log analysis on reading lists across a university, covering five years (2016 to 2020). We then used a questionnaire to gain feedback from academics about their experience with linking resources. Our results show a growing number of digital resources being used in reading lists, and indicate faculty-based differences in the types of resources linked. We also identify that many academics struggle with successfully linking resources, and do not perceive the process to be user friendly. The paper recommends a number of interventions to improve the reading list experience for academics.","PeriodicalId":112400,"journal":{"name":"2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127467877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Exploring the Classification of Traditional Chinese Bibliographies through Interactive Visualization 基于交互可视化的中国传统书目分类研究
2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL) Pub Date : 2021-09-01 DOI: 10.1109/JCDL52503.2021.00071
Wenqi Li, Fengxiang Wang, Jun Wang
{"title":"Exploring the Classification of Traditional Chinese Bibliographies through Interactive Visualization","authors":"Wenqi Li, Fengxiang Wang, Jun Wang","doi":"10.1109/JCDL52503.2021.00071","DOIUrl":"https://doi.org/10.1109/JCDL52503.2021.00071","url":null,"abstract":"Traditional Chinese bibliographies can be regarded as the earliest forms of knowledge organization system in China, which embed rich academic value and can reflect the knowledge, cultural, and political status at that time. This study adopts the digital humanities approach to investigate the bibliographies in a data-driven manner. We select seven representative traditional Chinese bibliographies and produced structured data by semiautomated methods. Interactive visualization is used as the main technique to provide both quantitative and qualitative view for humanities scholars to discover patterns, trends and anomalies in the change of the classification schemes of the traditional bibliographies. Examples are given to manifest how this interactive visualization can act as a tool to facilitate humanities research and provoke scholars thinking. We discuss the potential of the visualization technique to be used for studying traditional Chinese bibliographies and the embedded sociocultural implications.","PeriodicalId":112400,"journal":{"name":"2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130817261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
What Were People Searching For? A Query Log Analysis of An Academic Search Engine 人们在搜索什么?学术搜索引擎查询日志分析
2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL) Pub Date : 2021-09-01 DOI: 10.1109/JCDL52503.2021.00062
Shaurya Rohatgi, C. Lee Giles
{"title":"What Were People Searching For? A Query Log Analysis of An Academic Search Engine","authors":"Shaurya Rohatgi, C. Lee Giles","doi":"10.1109/JCDL52503.2021.00062","DOIUrl":"https://doi.org/10.1109/JCDL52503.2021.00062","url":null,"abstract":"Academic search engines have served the research community for years, yet there is little work done on understanding the taxonomy of query semantics. In this work, we present our findings of analyzing the query log of an academic search engine in the past four years. We study the distribution of query intents to understand the information requested by users. We classify query strings by topics using shallow and latent features captured using a customized word embedding model. To this end, we create a dataset that has scientific keywords and titles labeled with fields of study. This dataset is later used to train a classifier that discriminates query logs by topics. Our work will help to train better learning-based ranking functions that improve user experiences for an academic search engine. In addition, we anonymize our 14,759,852 query logs and make them available to the research community for further exploration.","PeriodicalId":112400,"journal":{"name":"2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129425709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Improved Discoverability of Digital Objects in Institutional Repositories Using Controlled Vocabularies 利用受控词汇表改进机构知识库中数字对象的可发现性
2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL) Pub Date : 2021-09-01 DOI: 10.1109/JCDL52503.2021.00022
Bertha Chipangila, Eric Liswaniso, Andrew Mawila, Philomena Mwanza, Daisy Nawila, Robert M'sendo, Mayumbo Nyirenda, Lighton Phiri
{"title":"Improved Discoverability of Digital Objects in Institutional Repositories Using Controlled Vocabularies","authors":"Bertha Chipangila, Eric Liswaniso, Andrew Mawila, Philomena Mwanza, Daisy Nawila, Robert M'sendo, Mayumbo Nyirenda, Lighton Phiri","doi":"10.1109/JCDL52503.2021.00022","DOIUrl":"https://doi.org/10.1109/JCDL52503.2021.00022","url":null,"abstract":"Higher Education Institutions (HEIs) utilise Institutional Repositories (IRs) to electronically store and make available scholarly research output produced by faculty staff and students. With the continued increase of scholarly research output produced, accurate and comprehensive association of subject headings to digital objects, during ingestion into IRs is crucial for effective discoverability of the objects and, additionally facilitating the discovery of related content. This paper outlines a case study conducted at an HEI-The University of Zambia-in order to demonstrate the effectiveness of integrating controlled subject vocabularies during the ingestion of digital objects in to IRs. A situational analysis was conducted to understand how subject headings are associated with digital objects and to analyse subject headings associated with already ingested digital objects. In addition, an exploratory study was conducted to determine domain-specific subject headings to be integrated with the IR. Furthermore, a usability study was conducted in order to comparatively determine the usefulness of using controlled vocabularies during the ingestion of digital objects into IRs. Finally, multi-label classification experiments were carried out where digital objects were assigned with more than one class. The results of the study revealed that the majority of digital objects are currently associated with two or less subject headings (71.2 %), with a significant number of subject headings (92.1 % being associated with a single publication, The comparative study suggests that IRs integrated with controlled vocabularies are perceived to be more usable (SUS Score = 68.9) when compared with IRs without controlled vocabularies (SUS Score = 66.2). The effectiveness of the multi-label arXiv subjects classifier demonstrates the viability of integrating automated techniques for subject classification.","PeriodicalId":112400,"journal":{"name":"2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121538131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Replaying Archived Twitter: When your bird is broken, will it bring you down? 当你的鸟坏了，它会把你打倒吗?
2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL) Pub Date : 2021-08-27 DOI: 10.1109/JCDL52503.2021.00028
Kritika Garg, Himarsha R. Jayanetti, Sawood Alam, Michele C. Weigle, Michael L. Nelson
{"title":"Replaying Archived Twitter: When your bird is broken, will it bring you down?","authors":"Kritika Garg, Himarsha R. Jayanetti, Sawood Alam, Michele C. Weigle, Michael L. Nelson","doi":"10.1109/JCDL52503.2021.00028","DOIUrl":"https://doi.org/10.1109/JCDL52503.2021.00028","url":null,"abstract":"Historians and researchers trust web archives to preserve social media content that no longer exists on the live web. However, what we see on the live web and how it is replayed in the archive are not always the same. In this paper, we document and analyze the problems in archiving Twitter ever since Twitter forced the use of its new UI in June 2020. Most web archives were unable to archive the new UI, resulting in archived Twitter pages displaying Twitter's “Something went wrong” error. The challenges in archiving the new UI forced web archives to continue using the old UI. To analyze the potential loss of information in web archival data due to this change, we used the personal Twitter account of the 45th President of the United States, @realDonaldTrump, which was suspended by Twitter on January 8, 2021. Trump's account was heavily labeled by Twitter for spreading misinformation, however we discovered that there is no evidence in web archives to prove that some of his tweets ever had a label assigned to them. We also studied the possibility of temporal violations in archived versions of the new UI, which may result in the replay of pages that never existed on the live web. Our goal is to educate researchers who may use web archives and caution them when drawing conclusions based on archived Twitter pages.","PeriodicalId":112400,"journal":{"name":"2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125042581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
ACM-CR: A Manually Annotated Test Collection for Citation Recommendation ACM-CR:引文推荐的手动注释测试集
2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL) Pub Date : 2021-08-17 DOI: 10.1109/JCDL52503.2021.00035
Florian Boudin
{"title":"ACM-CR: A Manually Annotated Test Collection for Citation Recommendation","authors":"Florian Boudin","doi":"10.1109/JCDL52503.2021.00035","DOIUrl":"https://doi.org/10.1109/JCDL52503.2021.00035","url":null,"abstract":"Citation recommendation is intended to assist researchers in the process of searching for relevant papers to cite by recommending appropriate citations for a given input text. Existing test collections for this task are noisy and unreliable since they are built automatically from parsed PDF papers. In this paper, we present our ongoing effort at creating a publicly available, manually annotated test collection for citation recommendation. We also conduct a series of experiments to evaluate the effectiveness of content-based baseline models on the test collection, providing results for future work to improve upon. Our test collection and code to replicate experiments are available at https://github.com/boudinfl/acm-cr","PeriodicalId":112400,"journal":{"name":"2021 ACM/IEEE Joint Conference on Digital Libraries (JCDL)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125474446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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