[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120920-en":3,"doc-seo-120920-105":30,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},120920,4398048949847,"Eliana","https://ap-avatar.wpscdn.com/avatar/400002536579ef2da7f?_k=1778318612642679267",6,"Technology","User Insights shaping Machine Learning applied to Archives","Archives contain extensive historical and cultural records, yet navigating them and extracting reliable knowledge is labor-intensive. Machine learning can unlock these archives, but impact depends on aligning ML capabilities with real user needs. This paper studies how user insights guide the development and deployment of ML for archival tasks, focusing on an iterative user-centered design process with editors and publishers who shape sorting and publication workflows. The approach highlights gaps between user expectations and functional integrity and supports user acceptance and empowerment.","User insights shaping machine learning applied to archives  \nKASTURI, Surya, SHENFIELD, Alex \u003C [http://orcid.org/0000-0002-2931-8077](http://orcid.org/0000-0002-2931-8077)> and ROAST, Christopher \u003C [http://orcid.org/0000-0002-6931-6252](http://orcid.org/0000-0002-6931-6252)>  \nAvailable from Sheffield Hallam University Research Archive (SHURA) at: [https://shura.shu.ac.uk/33786/](https://shura.shu.ac.uk/33786/)  \nThis document is the Accepted Version [AM]  \nCitation:  \nKASTURI, Surya, SHENFIELD, Alex and ROAST, Christopher (2024) . User insights shaping machine learning applied to archives. In: CONATI, Cristina, TORRE, Ilaria and VOLPE, Gualtiero,(eds.) AVI '24: Proceedings of the 2024 International Conference on Advanced Visual Interfaces. ACM. [Book Section]  \nCopyright and re-use policy  \nSee [http://shura.shu.ac.uk/information.html](http://shura.shu.ac.uk/information.html)  \nSheffield Hallam University Research Archive  \n[http://shura.shu.ac.uk](http://shura.shu.ac.uk)  \nUser Insights shaping Machine Learning applied to Archives  \nSurya Kasturi  \n[skasturi@microform.co.uk](skasturi@microform.co.uk)[ ](skasturi@microform.co.uk)[Microform Imaging ltd.](Microform Imaging ltd.)[ ](Microform Imaging ltd.)Wakefield, UK  \nChristopher Roast  \n[c.r.roast@shu.ac.uk](c.r.roast@shu.ac.uk)[ ](c.r.roast@shu.ac.uk)Sheffield Hallam University Sheffield, UK  \nAlex Shenfield  \n[a.shenfield@shu.ac.uk](a.shenfield@shu.ac.uk)[ ](a.shenfield@shu.ac.uk)Sheffield Hallam University Sheffield, UK  \nABSTRACT  \nArchives hold vast amounts of historical and cultural information, but navigating and extracting knowledge can be a daunting task. Machine learning (ML) offers immense potential to unlock these archives, yet its effectiveness hinges on understanding user needs. This paper explores how user insights can shape the development and application of ML in archives. Here “user” refers to editors and publishers who are crucial part of archival sorting and publication in the company. This paper emphasizes the importance of an iterative user centred design process to guide development and ensure user acceptance and empowerment. This approach reveals the distance between user expectations and functional integrity.  \nCCS CONCEPTS  \n• Human-centered computing → User centered design; Interface design prototyping; HCI theory, concepts and models; User interface design.  \nKEYWORDS  \nMachine Learning, user-centered designs, Archives, UI, UX  \nACM Reference Format:  \nSurya Kasturi, Christopher Roast, and Alex Shenfield. 2024. User Insights shaping Machine Learning applied to Archives. In International Conference on Advanced Visual Interfaces 2024 (AVI 2024), June 3–7, 2024, Arenzano, Genoa, Italy. ACM, New York, NY, USA, 3 pages. [https://doi.org/10.1145/](https://doi.org/10.1145/)[ ](https://doi.org/10.1145/)3656650.3656716  \n1 INTRODUCTION  \nThe application of Machine Learning (ML) techniques in archives has been a growing area of interest [1] . However, organizing and extracting knowledge for publication can be a time-consuming and laborious process for editors and publishers. In this case, a ML pipeline can help automate and enhance this process by providing text insights such as named entity recognition and copyright findings, as well as visual insights like object detection. The recent work in 2022 underscores the transformative potential of ML for extracting archival information and generating various metadata [5] . This metadata enrichment can improve discoverability and accessibility of archives. However, realising this potential in the form of a usable tool fit for editorial and publication purposes requires additional  \nPermission to make digital or hard copies of part or all ofthis work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must b","cbCaigmEPUkT0YgS","https://ap.wps.com/l/cbCaigmEPUkT0YgS","pdf",424437,1,4,"English","en",105,"# Abstract\n# Introduction\n# User-Centered Design Approach","[{\"question\":\"Why are user insights important for machine learning applied to archives?\",\"answer\":\"Because ML effectiveness depends on understanding user needs and publication workflows. The paper emphasizes user insights to guide development and ensure acceptance and empowerment.\"},{\"question\":\"How does the proposed approach involve users in ML development?\",\"answer\":\"It uses an iterative user-centered design process with editors and publishers, collecting continuous feedback to refine both the interface and ML experience.\"},{\"question\":\"What kinds of ML capabilities are discussed for archival tasks?\",\"answer\":\"A backend ML pipeline that supports text insights such as named entity recognition and copyright findings, along with visual insights like object detection.\"}]","User Insights shaping Machine Learning applied to Archives | PDF",1785732689,10,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":28},"user-insights-shaping-machine-learning-applied-to-archives","",{"@graph":36,"@context":84},[37,53,67],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/technology/",3,{"item":52,"name":13,"@type":43,"position":21},"https://docshare.wps.com/document/user-insights-shaping-machine-learning-applied-to-archives/120920/",{"url":52,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"Why are user insights important for machine learning applied to archives?","Question",{"text":74,"@type":75},"Because ML effectiveness depends on understanding user needs and publication workflows. The paper emphasizes user insights to guide development and ensure acceptance and empowerment.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"How does the proposed approach involve users in ML development?",{"text":79,"@type":75},"It uses an iterative user-centered design process with editors and publishers, collecting continuous feedback to refine both the interface and ML experience.",{"name":81,"@type":72,"acceptedAnswer":82},"What kinds of ML capabilities are discussed for archival tasks?",{"text":83,"@type":75},"A backend ML pipeline that supports text insights such as named entity recognition and copyright findings, along with visual insights like object detection.","https://schema.org",{"og:url":52,"og:type":86,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":88,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":91},[92,96,100,104,109,112,117,122,127,130,133],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":93,"show_sort_weight":94,"slug":95},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":97,"show_sort_weight":98,"slug":99},"Literature",80,"literature",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":101,"show_sort_weight":102,"slug":103},"Exam",70,"exam",{"id":105,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},5,"Comic",60,"comic",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":110,"slug":111},50,"technology",{"id":113,"doc_module":4,"doc_module_name":46,"category_name":114,"show_sort_weight":115,"slug":116},7,"Healthcare",40,"healthcare",{"id":118,"doc_module":4,"doc_module_name":46,"category_name":119,"show_sort_weight":120,"slug":121},8,"Research & Report",30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":29,"doc_module":4,"doc_module_name":46,"category_name":131,"show_sort_weight":29,"slug":132},"Lifestyle","lifestyle",{"id":134,"doc_module":4,"doc_module_name":46,"category_name":135,"show_sort_weight":105,"slug":136},19,"General","general"]