Deadline Further Extended: The Full Paper/Poster Submission Deadline has been further extended to March 30, 2026.
AII-EEKE 2026 Submit via OpenReview
AII-EEKE Joint Workshop

Joint Workshop of the 6th AI + Informetrics (AII) & the 7th Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE)
- AII-EEKE 2026

Affiliated with the 17th FLINS Conference & 21st ISKE Conference: Machine Learning and Knowledge Engineering for Decision Making (FLINS-ISKE 2026), Sydney, Australia.

Where
University of Technology Sydney (UTS) @ Sydney, Australia
When
15 July 2026

About the Workshop

Artificial intelligence (AI), particularly the increasing success of large language models (LLMs), is revolutionizing the research paradigm of scientometrics and informetrics, highlighting its incredible capabilities in scalable, effective, robust, and adaptable data analytics. AI-empowered informetric models have achieved significant accomplishments in the context of scientometric studies, e.g., supporting the design of scientometric research with insights, communicating the community by combining computational models and human knowledge, and developing adaptable analytical tools for deep literature analysis.

  • The AI + Informetrics (AII) Workshop series emphasizes endeavors in connecting AI and informetrics by constructing fundamental theories, developing novel methodologies, bridging conceptual knowledge with practical uses, and creating real-word solutions.

    • As one of the fundamental tasks in scientometrics, extracting useful knowledge entities from massive scientific data has been a long interest of the community, while the exponentially increased data volume and modality, the complicated real-world context of diverse knowledge entities, and the adaptability of rapidly developing AI techniques to actual information retrieval scenarios further obstacle a comprehensive solution.

  • The Extraction and Evaluation of Knowledge Entity (EEKE) Workshop series highlights the development of intelligent methods for identifying knowledge entities from scientific documents and promoting their application in broad information studies.

    • This joint workshop aims to engage the scientometrics community with broad open problems in AII and EEKE, foster interactive applications in the context of scientometrics, and gather researchers and practical users to open a collaborative platform for exchanging ideas, sharing pilot studies, and scoping future directions on this cutting-edge venue. We highlight the following core objectives:

  • Cohering AII-EEKE to fulfill cross-disciplinary gaps from either theoretical or practical perspectives
  • Developing advanced AII-EEKE models with enhanced capabilities in robustness, adaptability, and effectiveness.
  • Leveraging knowledge, concepts, and models in information management to strengthen the interpretability of AII-EEKE to adapt to empirical needs in real-world cases.

    • Call for Papers

    This workshop is primarily designed for academic researchers in broad information and library sciences, science of science, artificial intelligence, and will also be of interest to librarians, ST&I administrators and policymakers, and practitioners in any related sectors. We invite stimulating research on topics including, but not limited to, methods of knowledge entity extraction and applications of knowledge entity. Specific examples of fields of interest include:

    • Bibliometrics/Scientometrics/Informetrics with large language models
    • Bibliometrics/Scientometrics/Informetrics with machine learning (including deep learning)
    • Bibliometrics/Scientometrics/Informetrics with natural language processing or computational linguistics
    • Bibliometrics/Scientometrics/Informetrics with computer vision
    • Bibliometrics/Scientometrics/Informetrics with other related AI techniques (e.g., information retrieval)
    • Task and methodology entity extraction from scientific documents
    • Model and algorithmize entity extraction from scientific documents
    • Dataset and metrics mention extraction from scientific documents
    • Software and tool extraction from scientific documents
    • Knowledge entity summarization
    • Relation extraction of knowledge entity
    • Modeling function of knowledge entity citation
    • AI for science of science
    • AI for science, technology, & innovation
    • AI for research policy and strategic management
    • Application of knowledge entity extraction
    • Applications of AI-empowered informetrics

    Special Issue Opportunity: High-quality and relevant submissions to this workshop will be recommended for the Technological Forecasting and Social Change (TFSC) Special Issue:

    “Large Language Models as Methodological Innovators: Advancing Theory and Practice in Technology Management”

    All attendees are encouraged to attend the associated TFSC Paper Development Workshop.

    TFSC Paper Development Workshop

    Keynote

    Professor Lisa M. Given
    Invited Speaker

    Distinguished Professor Lisa M. Given

    RMIT University, Melbourne

    On Users, Use Cases, and the “Real World” in AI Research: An Interdisciplinary Imperative

    Distinguished Professor Lisa M. Given (FASSA, FASIS&T) is Director of the Centre for Human-AI Information Environments, Director of the Social Change Enabling Impact Platform, and Distinguished Professor of Information Sciences at RMIT University (Melbourne). A Fellow of the Academy of the Social Sciences in Australia, her interdisciplinary research in human information behaviour brings a critical, social research lens to technology use and human centred design. Her studies embed social change, in workplaces and everyday life.

    A Fellow, and former President, of the Association for Information Science and Technology (ASIS&T), she is Editor-in-Chief of the Journal of the Association for Information Science and Technology (JASIST) and lead author of Looking for Information: Examining Research on How People Engage with Information (2023).

    Read more about Lisa Given

    Programme

    To be announced soon.

    Submission Information

    Submissions must be written in English and prepared using the Springer Lecture Notes in Computer Science (LNCS) template. Manuscripts should be submitted in PDF format via OpenReview.

    All accepted papers for the AII-EEKE workshop will be published as proceedings by Springer.

    All accepted papers must be presented in person by at least one registered author.

    Paper types and length requirements (excluding references):

    Submit via OpenReview Download Template - Word Download Template - Latex Template Instructions

    Important Dates (AoE)

    MilestoneDate
    Paper Submissions Open on OpenReviewDecember 22, 2025
    Full Paper/Poster Submission DeadlineMarch 1, 2026 March 15, 2026 March 30, 2026
    Full Paper/Poster Acceptance NotificationApril 20, 2026
    Camera-ready Paper Submission DeadlineMay 5, 2026
    Workshop DateJuly 15, 2026

    Chairs & Committees

    General Chairs

    Yi Zhang

    		Yi Zhang (yi.zhang@uts.edu.au) is an Associate Professor at the Australian Artificial Intelligence Institute, University of Technology Sydney. He holds dual Ph.D. degrees in Management Science & Engineering and in Software Engineering. His research interests align with intelligent bibliometrics - incorporating artificial intelligence and data science techniques with bibliometric indicators for broad science, technology & innovation studies. He is the recipient of the 2019 Discovery Early Career Researcher Award granted by the Australian Research Council. He serves as the Executive Editor for Technological Forecasting & Social Change, Associate Editor for the IEEE Transactions on Engineering Management and Scientometrics, and the Specialty Chief Editor for Frontiers in Research Metrics and Analytics.

    Chengzhi Zhang

    		Chengzhi Zhang (zhangcz@njust.edu.cn) is a professor of Department of Information Management, Nanjing University of Science and Technology, China. He received his PhD degree of Information Science from Nanjing University, China. He has published more than 100 publications, including JASIST, IPM, LISR, TFSC, Aslib JIM, JOI, OIR, SCIM, ACL, NAACL, etc. His current research interests include scientific text mining, knowledge entity extraction and evaluation, social media mining. He serves as Editorial Board Member and Managing Guest Editor for 10 international journals (Patterns, IPM, SCIM, OIR, Aslib JIM, TEL, JDIS, DIM, DI, etc.) and PC members of several international conferences in fields of natural language process and scientometrics.

    Philipp Mayr

    		Philipp Mayr (philipp.mayr@gesis.org) is a team leader at the GESIS - Leibniz-Institute for the Social Sciences department Knowledge Technologies for the Social Sciences (WTS). He received his PhD in applied informetrics and information retrieval from the Berlin School of Library and Information Science at Humboldt University Berlin. He has published in top conferences and prestigious journals in the areas informetrics, information retrieval and digital libraries. His research group focuses on methods and techniques for interactive information retrieval and data set search. He was the main organizer of the BIR workshops at ECIR 2014-2021 and the BIRNDL workshops at JCDL 2016 and SIGIR 2017-2019.

     

    Organization Committee

    Wei Lu

    		Wei Lu (weilu@whu.edu.cn) is a professor of School of Information Management and director of Information Retrieval and Knowledge Mining Center, Wuhan University. He received his PhD degree of Information Science from Wuhan University, China. His current research interests include information retrieval, text mining, QA etc. He has papers published on SIGIR, Information Sciences, JASIT, Journal of Information Science etc. He serves as diverse roles (e.g., Associate Editor, Editorial Board Member, and Managing Guest Editor) for several journals.

    Ying Ding

    		Ying Ding (ying.ding@austin.utexas.edu)is Bill & Lewis Suit professor at School of Information, University of Texas at Austin. She has been involved in various NIH, NSF and European-Union funded projects. She has published 240+ papers in journals, conferences, and workshops, and served as the program committee member for 200+ international conferences. She is the co-editor of book series called Semantic Web Synthesis by Morgan & Claypool publisher, the co-editor-in-chief for Data Intelligence published by MIT Press and Chinese Academy of Sciences, and serves as the editorial board member for several top journals in Information Science and Semantic Web. Her current research interests include data-driven science of science, AI in healthcare, Semantic Web, knowledge graph, data science, scholarly communication, and the application of Web technologies.

    Arho Suominen

    		Arho Suominen (Arho.Suominen@vtt.fi) is principal scientist at the VTT Technical Research Centre of Finland and Industrial professor at Tampere University (Finland). Dr. Suominen’s research focuses on qualitative and quantitative assessment of innovation systems with a special focus on quantitative methods. His prior research has been funded by the European Commission via H2020, Academy of Finland, Finnish Funding Agency for Technology, Turku University Foundation and the Fulbright Center Finland. Through the Fulbright program, he worked as Visiting Scholar at the School of Public Policy at the Georgia Institute of Technology. Dr. Suominen has a Doctor of Science (Tech.) degree from the University of Turku and holds an Officers basic degree from the National Defence University of Finland.

    Haihua Chen

    		Haihua Chen (haihua.chen@unt.edu) is an assistant professor in the Departmentof Information Science at the University of North Texas. He has expertise in applied data science, natural language processing, information retrieval, and text mining. He co-authored more than 40 publications in academic venues in both information science and computer science. He is serving as co-editor for The Electronic Library, the guest editor of Information Discovery & Delivery and Frontiers in Big Data special issues, and the reviewer for 14 peer reviewed journals and several international conferences.

    Programme Committee

    NameAffiliation
    Alireza AbbasiUniversity of New South Wales (Canberra)
    Iana AtanassovaCRIT, Université de Bourgogne Franche-Comté
    Marc BertinUniversité Claude Bernard Lyon 1
    Katarina BolandGESIS - Leibniz Institute for the Social Sciences
    Yi BuPeking University
    Guillaume CabanacIRIT - Université Paul Sabatier Toulouse 3
    Caitlin CassidySearch Technology Inc
    Chong ChenBeijing Normal University
    Guo ChenNanjing University of Science and Technology
    Hongshu ChenBeijing Institute of Technology
    Gong ChengNanjing University
    Jian DuPeking University
    Edward FoxVirginia Tech
    Ying GuoChina University of Political Science and Law
    Arash HajikhaniVTT Technical Research Centre of Finland
    Jiangen HeUniversity of Tennessee
    Jianhua HouSun Yat-sen University
    Zhigang HuSouth China Normal University
    Bolin HuaPeking University
    Lu HuangBeijing Institute of Technology
    Ying HuangWuhan University
    Yong HuangWuhan University
    Yuya KajikawaTokyo University of Technology
    Vivek Kumar SinghBanaras Hindu University, Varanasi, India
    Chenliang LiWuhan University
    Kai LiUniversity of Tennessee
    Chao LuHohai University
    Shutian MaTencent
    Jin MaoWuhan University
    Xianling MaoBeijing Institute of Technology
    Chao MinNanjing University
    Wolfgang OttoGESIS - Leibniz Institute for the Social Sciences
    Xuelian PanNanjing University
    Dwaipayan RoyGESIS - Leibniz Institute for the Social Sciences
    Philipp SchaerTH Köln (University of Applied Sciences)
    Mayank SinghIIT Gandhinagar
    Bart ThijsECOOM, MSI, KU Leuven
    Suppawong TuarobMahidol University
    Dongbo WangNanjing Agricultural University
    Xuefeng WangBeijing Institute of Technology
    Yuzhuo WangAnhui University
    Dietmar WolframUniversity of Wisconsin-Milwaukee
    Jian WuOld Dominion University
    Mengjia WuUniversity of Technology Sydney
    Tianxing WuSoutheast University
    Xiaolan WuNanjing Normal University
    Yanghua XiaoFudan University
    Jian XuSun Yat-sen University
    Shuo XuBeijing University of Technology
    Erjia YanDrexel University
    Heng ZhangCentral China Normal University
    Jinzhu ZhangNanjing University of Science and Technology
    Xiaojuan ZhangSouthwest University
    Yingyi ZhangSoochow University
    Zhixiong ZhangNational Science Library, Chinese Academy of Sciences
    Qingqing ZhouNanjing Normal University
    Yongjun ZhuYonsei University

    References

    1. Chang, X., Zheng, Q. (2008). Knowledge Element Extraction for Knowledge-Based Learning Resources Organization. Advances in Web Based Learning - ICWL 2007, LNCS 4823. Springer. https://doi.org/10.1007/978-3-540-78139-4_10
    2. Ying, D., Min, S., Jia, H., Qi, Y., Erjia, Y., Lili, L., Tamy, C. (2013). entitymetrics: measuring the impact of entities. PLOS ONE, 8(8), e71416. https://doi.org/10.1371/journal.pone.0071416
    3. Zhang, C., Mayr, P., Lu, W., & Zhang, Y. (2022). JCDL2022 workshop: EEKE2022. JCDL ’22, Article 54, 1-2. https://doi.org/10.1145/3529372.3530917
    4. Zhang, Y., Zhang, C., Mayr, P., & Suominen, A. (2022). An editorial of “AI + informetrics”. Scientometrics, 127, 6503-6507. https://doi.org/10.1007/s11192-022-04561-w

    Past Proceedings & Journal Special Issues

    Proceedings

    Special Issues (EEKE-related)

    Special Issues (AI + Informetrics)