arXiv - CS - Digital Libraries最新文献_第3页

Examining Different Research Communities: Authorship Network 研究不同的研究社区：作者网络

arXiv - CS - Digital Libraries Pub Date : 2024-08-24 DOI: arxiv-2409.00081

Shrabani Ghosh

引用次数: 0

LCA and energy efficiency in buildings: mapping more than twenty years of research 生命周期评估与建筑能效：二十多年的研究图谱

arXiv - CS - Digital Libraries Pub Date : 2024-08-23 DOI: arxiv-2409.00065

F. Asdrubali, A. Fronzetti Colladon, L. Segneri, D. M. Gandola

{"title":"LCA and energy efficiency in buildings: mapping more than twenty years of research","authors":"F. Asdrubali, A. Fronzetti Colladon, L. Segneri, D. M. Gandola","doi":"arxiv-2409.00065","DOIUrl":"https://doi.org/arxiv-2409.00065","url":null,"abstract":"Research on Life Cycle Assessment (LCA) is being conducted in various\u0000sectors, from analyzing building materials and components to comprehensive\u0000evaluations of entire structures. However, reviews of the existing literature\u0000have been unable to provide a comprehensive overview of research in this field,\u0000leaving scholars without a definitive guideline for future investigations. This\u0000paper aims to fill this gap, mapping more than twenty years of research. Using\u0000an innovative methodology that combines social network analysis and text\u0000mining, the paper examined 8024 scientific abstracts. The authors identified\u0000seven key thematic groups, building and sustainability clusters (BSCs). To\u0000assess their significance in the broader discourse on building and\u0000sustainability, the semantic brand score (SBS) indicator was applied.\u0000Additionally, building and sustainability trends were tracked, focusing on the\u0000LCA concept. The major research topics mainly relate to building materials and\u0000energy efficiency. In addition to presenting an innovative approach to\u0000reviewing extensive literature domains, the article also provides insights into\u0000emerging and underdeveloped themes, outlining crucial future research\u0000directions.","PeriodicalId":501285,"journal":{"name":"arXiv - CS - Digital Libraries","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142219110","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

Towards a Knowledge Graph for Models and Algorithms in Applied Mathematics 建立应用数学模型和算法的知识图谱

arXiv - CS - Digital Libraries Pub Date : 2024-08-19 DOI: arxiv-2408.10003

Björn Schembera, Frank Wübbeling, Hendrik Kleikamp, Burkhard Schmidt, Aurela Shehu, Marco Reidelbach, Christine Biedinger, Jochen Fiedler, Thomas Koprucki, Dorothea Iglezakis, Dominik Göddeke

{"title":"Towards a Knowledge Graph for Models and Algorithms in Applied Mathematics","authors":"Björn Schembera, Frank Wübbeling, Hendrik Kleikamp, Burkhard Schmidt, Aurela Shehu, Marco Reidelbach, Christine Biedinger, Jochen Fiedler, Thomas Koprucki, Dorothea Iglezakis, Dominik Göddeke","doi":"arxiv-2408.10003","DOIUrl":"https://doi.org/arxiv-2408.10003","url":null,"abstract":"Mathematical models and algorithms are an essential part of mathematical\u0000research data, as they are epistemically grounding numerical data. In order to\u0000represent models and algorithms as well as their relationship semantically to\u0000make this research data FAIR, two previously distinct ontologies were merged\u0000and extended, becoming a living knowledge graph. The link between the two\u0000ontologies is established by introducing computational tasks, as they occur in\u0000modeling, corresponding to algorithmic tasks. Moreover, controlled vocabularies\u0000are incorporated and a new class, distinguishing base quantities from specific\u0000use case quantities, was introduced. Also, both models and algorithms can now\u0000be enriched with metadata. Subject-specific metadata is particularly relevant\u0000here, such as the symmetry of a matrix or the linearity of a mathematical\u0000model. This is the only way to express specific workflows with concrete models\u0000and algorithms, as the feasible solution algorithm can only be determined if\u0000the mathematical properties of a model are known. We demonstrate this using two\u0000examples from different application areas of applied mathematics. In addition,\u0000we have already integrated over 250 research assets from applied mathematics\u0000into our knowledge graph.","PeriodicalId":501285,"journal":{"name":"arXiv - CS - Digital Libraries","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142219112","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

Can we measure the impact of a database? 我们能否衡量数据库的影响？

arXiv - CS - Digital Libraries Pub Date : 2024-08-19 DOI: arxiv-2408.09842

Peter Buneman, Dennis Dosso, Matteo Lissandrini, Gianmaria Silvello, He Sun

引用次数: 0

Creating Publishing Accounts for University Professors on Global Scientific Websites (ORCID, Research Gate, Google Scholar) 在全球科学网站（ORCID、Research Gate、Google Scholar）上为大学教授创建出版账户

arXiv - CS - Digital Libraries Pub Date : 2024-08-16 DOI: arxiv-2408.08936

Ahmed Shaker Alalaq

引用次数: 0

An Analysis of the Impact of Gold Open Access Publications in Computer Science 计算机科学领域开放获取金牌出版物的影响分析

arXiv - CS - Digital Libraries Pub Date : 2024-08-15 DOI: arxiv-2408.10262

Padraig Cunningham, Barry Smyth

引用次数: 0

NeuroPapyri: A Deep Attention Embedding Network for Handwritten Papyri Retrieval 神经纸莎草纸：用于手写纸莎草纸检索的深度注意力嵌入网络

arXiv - CS - Digital Libraries Pub Date : 2024-08-14 DOI: arxiv-2408.07785

Giuseppe De Gregorio, Simon Perrin, Rodrigo C. G. Pena, Isabelle Marthot-Santaniello, Harold Mouchère

{"title":"NeuroPapyri: A Deep Attention Embedding Network for Handwritten Papyri Retrieval","authors":"Giuseppe De Gregorio, Simon Perrin, Rodrigo C. G. Pena, Isabelle Marthot-Santaniello, Harold Mouchère","doi":"arxiv-2408.07785","DOIUrl":"https://doi.org/arxiv-2408.07785","url":null,"abstract":"The intersection of computer vision and machine learning has emerged as a\u0000promising avenue for advancing historical research, facilitating a more\u0000profound exploration of our past. However, the application of machine learning\u0000approaches in historical palaeography is often met with criticism due to their\u0000perceived ``black box'' nature. In response to this challenge, we introduce\u0000NeuroPapyri, an innovative deep learning-based model specifically designed for\u0000the analysis of images containing ancient Greek papyri. To address concerns\u0000related to transparency and interpretability, the model incorporates an\u0000attention mechanism. This attention mechanism not only enhances the model's\u0000performance but also provides a visual representation of the image regions that\u0000significantly contribute to the decision-making process. Specifically\u0000calibrated for processing images of papyrus documents with lines of handwritten\u0000text, the model utilizes individual attention maps to inform the presence or\u0000absence of specific characters in the input image. This paper presents the\u0000NeuroPapyri model, including its architecture and training methodology. Results\u0000from the evaluation demonstrate NeuroPapyri's efficacy in document retrieval,\u0000showcasing its potential to advance the analysis of historical manuscripts.","PeriodicalId":501285,"journal":{"name":"arXiv - CS - Digital Libraries","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142219119","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

Optical Music Recognition in Manuscripts from the Ricordi Archive 里科迪档案馆手稿中的光学音乐识别技术

arXiv - CS - Digital Libraries Pub Date : 2024-08-14 DOI: arxiv-2408.10260

Federico Simonetta, Rishav Mondal, Luca Andrea Ludovico, Stavros Ntalampiras

引用次数: 0

A New Framework for Error Analysis in Computational Paleographic Dating of Greek Papyri 希腊纸质古籍计算年代误差分析新框架

arXiv - CS - Digital Libraries Pub Date : 2024-08-14 DOI: arxiv-2408.07779

Giuseppe De Gregorio, Lavinia Ferretti, Rodrigo C. G. Pena, Isabelle Marthot-Santaniello, Maria Konstantinidou, John Pavlopoulos

{"title":"A New Framework for Error Analysis in Computational Paleographic Dating of Greek Papyri","authors":"Giuseppe De Gregorio, Lavinia Ferretti, Rodrigo C. G. Pena, Isabelle Marthot-Santaniello, Maria Konstantinidou, John Pavlopoulos","doi":"arxiv-2408.07779","DOIUrl":"https://doi.org/arxiv-2408.07779","url":null,"abstract":"The study of Greek papyri from ancient Egypt is fundamental for understanding\u0000Graeco-Roman Antiquity, offering insights into various aspects of ancient\u0000culture and textual production. Palaeography, traditionally used for dating\u0000these manuscripts, relies on identifying chronologically relevant features in\u0000handwriting styles yet lacks a unified methodology, resulting in subjective\u0000interpretations and inconsistencies among experts. Recent advances in digital\u0000palaeography, which leverage artificial intelligence (AI) algorithms, have\u0000introduced new avenues for dating ancient documents. This paper presents a\u0000comparative analysis between an AI-based computational dating model and human\u0000expert palaeographers, using a novel dataset named Hell-Date comprising\u0000securely fine-grained dated Greek papyri from the Hellenistic period. The\u0000methodology involves training a convolutional neural network on visual inputs\u0000from Hell-Date to predict precise dates of papyri. In addition, experts provide\u0000palaeographic dating for comparison. To compare, we developed a new framework\u0000for error analysis that reflects the inherent imprecision of the palaeographic\u0000dating method. The results indicate that the computational model achieves\u0000performance comparable to that of human experts. These elements will help\u0000assess on a more solid basis future developments of computational algorithms to\u0000date Greek papyri.","PeriodicalId":501285,"journal":{"name":"arXiv - CS - Digital Libraries","volume":"60 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142219116","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

Evaluating Research Quality with Large Language Models: An Analysis of ChatGPT's Effectiveness with Different Settings and Inputs 评估大型语言模型的研究质量：不同设置和输入下 ChatGPT 的有效性分析

arXiv - CS - Digital Libraries Pub Date : 2024-08-13 DOI: arxiv-2408.06752

Mike Thelwall

{"title":"Evaluating Research Quality with Large Language Models: An Analysis of ChatGPT's Effectiveness with Different Settings and Inputs","authors":"Mike Thelwall","doi":"arxiv-2408.06752","DOIUrl":"https://doi.org/arxiv-2408.06752","url":null,"abstract":"Evaluating the quality of academic journal articles is a time consuming but\u0000critical task for national research evaluation exercises, appointments and\u0000promotion. It is therefore important to investigate whether Large Language\u0000Models (LLMs) can play a role in this process. This article assesses which\u0000ChatGPT inputs (full text without tables, figures and references; title and\u0000abstract; title only) produce better quality score estimates, and the extent to\u0000which scores are affected by ChatGPT models and system prompts. The results\u0000show that the optimal input is the article title and abstract, with average\u0000ChatGPT scores based on these (30 iterations on a dataset of 51 papers)\u0000correlating at 0.67 with human scores, the highest ever reported. ChatGPT 4o is\u0000slightly better than 3.5-turbo (0.66), and 4o-mini (0.66). The results suggest\u0000that article full texts might confuse LLM research quality evaluations, even\u0000though complex system instructions for the task are more effective than simple\u0000ones. Thus, whilst abstracts contain insufficient information for a thorough\u0000assessment of rigour, they may contain strong pointers about originality and\u0000significance. Finally, linear regression can be used to convert the model\u0000scores into the human scale scores, which is 31% more accurate than guessing.","PeriodicalId":501285,"journal":{"name":"arXiv - CS - Digital Libraries","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142219118","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