Proceedings of the 21st ACM Symposium on Document Engineering最新文献_第3页

Small-step pipelines reduce the complexity of XSLT/XPath programs 小步骤管道降低了XSLT/XPath程序的复杂性

Proceedings of the 21st ACM Symposium on Document Engineering Pub Date : 2021-08-16 DOI: 10.1145/3469096.3474922

Marcel Schaeben, Gioele Barabucci

引用次数: 0

Table-structure recognition method using neural networks for implicit ruled line estimation and cell estimation 表结构识别方法采用神经网络进行隐式直纹线估计和单元估计

Proceedings of the 21st ACM Symposium on Document Engineering Pub Date : 2021-08-16 DOI: 10.1145/3469096.3469870

Manabu Ohta, R. Yamada, T. Kanazawa, A. Takasu

引用次数: 2

Session details: Collections, systems and management 会话细节:集合、系统和管理

Proceedings of the 21st ACM Symposium on Document Engineering Pub Date : 2021-08-16 DOI: 10.1145/3482787

Angelo Di Iorio

引用次数: 0

20 years of physical document and product protection using digital methods 使用数字方法进行20年的物理文档和产品保护

Proceedings of the 21st ACM Symposium on Document Engineering Pub Date : 2021-08-16 DOI: 10.1145/3469096.3476452

J. Picard

引用次数: 1

Trustworthiness of spam email addresses using machine learning 使用机器学习的垃圾邮件地址的可信度

Proceedings of the 21st ACM Symposium on Document Engineering Pub Date : 2021-08-16 DOI: 10.1145/3469096.3475060

Francisco Jáñez-Martino, R. Alaíz-Rodríguez, V. González-Castro, Eduardo FIDALGO

{"title":"Trustworthiness of spam email addresses using machine learning","authors":"Francisco Jáñez-Martino, R. Alaíz-Rodríguez, V. González-Castro, Eduardo FIDALGO","doi":"10.1145/3469096.3475060","DOIUrl":"https://doi.org/10.1145/3469096.3475060","url":null,"abstract":"Cybercriminals have increasingly used spam email to send scams, phishing, malware and other frauds to organisations and people. They design sophisticated and contextualised emails to make them look trustworthy for users, being the sender addresses an essential part. Although cybersecurity agencies and companies develop products and organise courses for people to detect emails patterns, spam attacks are not totally avoided yet. This work presents a proof-of-concept methodology to give the user more meaningful information about trustworthiness to detect these harmful emails. For the first time in the literature, we present an email address dataset manually labelled into two classes, low and high quality. Moreover, we extracted 18 handcrafted features based on social engineering techniques and natural language properties. We evaluated four popular machine learning classifiers and obtained the best performance with Naive Bayes, i.e., 88.17% of accuracy and 0.808 of F1-Score. Additionally, we applied the InterpretML framework to find out the most relevant properties to eventually implement an automatic system able to inform about the trustworthiness of email addresses.","PeriodicalId":423462,"journal":{"name":"Proceedings of the 21st ACM Symposium on Document Engineering","volume":"222 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132384759","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 of the 21st ACM Symposium on Document Engineering 第21届美国计算机学会文献工程研讨会论文集

Proceedings of the 21st ACM Symposium on Document Engineering Pub Date : 2021-08-16 DOI: 10.1145/3469096

引用次数: 0

SlideGen

Proceedings of the 21st ACM Symposium on Document Engineering Pub Date : 2021-08-16 DOI: 10.1145/3469096.3474939

Athar Sefid, Prasenjit K. Mitra, Lee Giles

引用次数: 5

Session details: Generation, manipulation and presentation 会话细节:生成、操作和表示

Proceedings of the 21st ACM Symposium on Document Engineering Pub Date : 2021-08-16 DOI: 10.1145/3482782

S. Bagley

引用次数: 0

Session details: Keynote II 会议详情:主题演讲二

Proceedings of the 21st ACM Symposium on Document Engineering Pub Date : 2021-08-16 DOI: 10.1145/3482783

S. Simske

引用次数: 0

ALiBERT

Proceedings of the 21st ACM Symposium on Document Engineering Pub Date : 2021-08-16 DOI: 10.1145/3469096.3474928

Rajkumar Ramamurthy, Maren Pielka, Robin Stenzel, Christian Bauckhage, R. Sifa, T. Khameneh, Ulrich Warning, Bernd Kliem, Rüdiger Loitz

{"title":"ALiBERT","authors":"Rajkumar Ramamurthy, Maren Pielka, Robin Stenzel, Christian Bauckhage, R. Sifa, T. Khameneh, Ulrich Warning, Bernd Kliem, Rüdiger Loitz","doi":"10.1145/3469096.3474928","DOIUrl":"https://doi.org/10.1145/3469096.3474928","url":null,"abstract":"We consider Automated List Inspection (ALI), a content-based text recommendation system that assists auditors in matching relevant text passages from notes in financial statements to specific law regulations. ALI follows a ranking paradigm in which a fixed number of requirements per textual passage are shown to the user. Despite achieving impressive ranking performance, the user experience can still be improved by showing a dynamic number of recommendations. Besides, existing models rely on a feature-based language model that needs to be pre-trained on a large corpus of domain-specific datasets. Moreover, they cannot be trained in an end-to-end fashion by jointly optimizing with language model parameters. In this work, we alleviate these concerns by considering a multi-label classification approach that predicts dynamic requirement sequences. We base our model on pre-trained BERT that allows us to fine-tune the whole model in an end-to-end fashion, thereby avoiding the need for training a language representation model. We conclude by presenting a detailed evaluation of the proposed model on two German financial datasets.","PeriodicalId":423462,"journal":{"name":"Proceedings of the 21st ACM Symposium on Document Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127622202","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: 11