Italian Research Conference on Digital Library Management Systems最新文献

(Semi)automated disambiguation of scholarly repositories 学术知识库的(半)自动化消歧

Italian Research Conference on Digital Library Management Systems Pub Date : 2023-07-05 DOI: 10.48550/arXiv.2307.02647

Miriam Baglioni, A. Mannocci, Gina Pavone, M. Bonis, P. Manghi

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引用次数: 1

Grimm in Wonderland: Prompt Engineering with Midjourney to Illustrate Fairytales 格林在仙境:提示工程与Midjourney来说明童话

Italian Research Conference on Digital Library Management Systems Pub Date : 2023-02-17 DOI: 10.48550/arXiv.2302.08961

M. Ruskov

{"title":"Grimm in Wonderland: Prompt Engineering with Midjourney to Illustrate Fairytales","authors":"M. Ruskov","doi":"10.48550/arXiv.2302.08961","DOIUrl":"https://doi.org/10.48550/arXiv.2302.08961","url":null,"abstract":"The quality of text-to-image generation is continuously improving, yet the boundaries of its applicability are still unclear. In particular, refinement of the text input with the objective of achieving better results - commonly called prompt engineering - so far seems to have not been geared towards work with pre-existing texts. We investigate whether text-to-image generation and prompt engineering could be used to generate basic illustrations of popular fairytales. Using Midjourney v4, we engage in action research with a dual aim: to attempt to generate 5 believable illustrations for each of 5 popular fairytales, and to define a prompt engineering process that starts from a pre-existing text and arrives at an illustration of it. We arrive at a tentative 4-stage process: i) initial prompt, ii) composition adjustment, iii) style refinement, and iv) variation selection. We also discuss three reasons why the generation model struggles with certain illustrations: difficulties with counts, bias from stereotypical configurations and inability to depict overly fantastic situations. Our findings are not limited to the specific generation model and are intended to be generalisable to future ones.","PeriodicalId":108702,"journal":{"name":"Italian Research Conference on Digital Library Management Systems","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125404259","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: 3

CTE: A Dataset for Contextualized Table Extraction CTE:用于上下文化表提取的数据集

Italian Research Conference on Digital Library Management Systems Pub Date : 2023-02-02 DOI: 10.48550/arXiv.2302.01451

Andrea Gemelli, Emanuele Vivoli, S. Marinai

{"title":"CTE: A Dataset for Contextualized Table Extraction","authors":"Andrea Gemelli, Emanuele Vivoli, S. Marinai","doi":"10.48550/arXiv.2302.01451","DOIUrl":"https://doi.org/10.48550/arXiv.2302.01451","url":null,"abstract":"Relevant information in documents is often summarized in tables, helping the reader to identify useful facts. Most benchmark datasets support either document layout analysis or table understanding, but lack in providing data to apply both tasks in a unified way. We define the task of Contextualized Table Extraction (CTE), which aims to extract and define the structure of tables considering the textual context of the document. The dataset comprises 75k fully annotated pages of scientific papers, including more than 35k tables. Data are gathered from PubMed Central, merging the information provided by annotations in the PubTables-1M and PubLayNet datasets. The dataset can support CTE and adds new classes to the original ones. The generated annotations can be used to develop end-to-end pipelines for various tasks, including document layout analysis, table detection, structure recognition, and functional analysis. We formally define CTE and evaluation metrics, showing which subtasks can be tackled, describing advantages, limitations, and future works of this collection of data. Annotations and code will be accessible a https://github.com/AILab-UniFI/cte-dataset.","PeriodicalId":108702,"journal":{"name":"Italian Research Conference on Digital Library Management Systems","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132574343","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

FullBrain: a Social E-learning Platform FullBrain:一个社会化的电子学习平台

Italian Research Conference on Digital Library Management Systems Pub Date : 2022-12-01 DOI: 10.48550/arXiv.2212.01387

M. Biasini, Vittorio Carmignani, N. Ferro, Panagiotis Filianos, Maria Maistro, Giorgio Maria Di Nunzio

引用次数: 4

Identifying, Classifying and Searching Graphic Symbols in the NOTAE System NOTAE系统中图形符号的识别、分类和检索

Italian Research Conference on Digital Library Management Systems Pub Date : 2020-01-30 DOI: 10.1007/978-3-030-39905-4_12

M. Boccuzzi, T. Catarci, Luca Deodati, Andrea Fantoli, A. Ghignoli, F. Leotta, Massimo Mecella, A. Monte, Nina Sietis

引用次数: 4

Re-implementing and Extending Relation Network for R-CBIR R-CBIR关系网络的再实现与扩展

Italian Research Conference on Digital Library Management Systems Pub Date : 2020-01-30 DOI: 10.1007/978-3-030-39905-4_9

Nicola Messina, G. Amato, F. Falchi

引用次数: 2

Reproducibility of the Neural Vector Space Model via Docker 通过Docker的神经向量空间模型的再现性

Italian Research Conference on Digital Library Management Systems Pub Date : 2020-01-30 DOI: 10.1007/978-3-030-39905-4_1

N. Ferro, S. Marchesin, Alberto Purpura, G. Silvello

引用次数: 0

TindArt, an Experiment on User Profiling for Museum Applications TindArt，博物馆应用程序的用户分析实验

Italian Research Conference on Digital Library Management Systems Pub Date : 2020-01-30 DOI: 10.1007/978-3-030-39905-4_13

Daniel Zilio, N. Orio, Camilla Toniolo

引用次数: 1

3D Average Common Submatrix Measure 3D平均公子矩阵测量

Italian Research Conference on Digital Library Management Systems Pub Date : 2020-01-30 DOI: 10.1007/978-3-030-39905-4_4

Federica Franco, Alessia Amelio, S. Greco

引用次数: 0

Recognition of Concordances for Indexing in Digital Libraries 数字图书馆标引中的一致性识别

Italian Research Conference on Digital Library Management Systems Pub Date : 2020-01-30 DOI: 10.1007/978-3-030-39905-4_14

S. Marinai, Samuele Capobianco, Zahra Ziran, A. Giuntini, Pierluigi Mansueto

引用次数: 0