KDAH-CIKM is traditionally recognized as a workshop in ACM CIKM for past few years (starting from 2018, with a break in 2022) that inculcates the positive social impact in knowledge-driven analytics research. KDAH-CIKM is traditionally recognized as a workshop in ACM CIKM for past two years that inculcates the positive social impact in knowledge-driven analytics research. This workshop is about illustrating how knowledge-based analytics can be used to create applications that are tailored to people and their needs. We'll be talking about agent-based modeling, machine learning, deep learning, creating causal models, AI that can explain things, fairness and game theory, and planning. We'll also be looking at neuro-synthetic AI and related technologies. We want to show how knowledge-driven people, societies and technologies can all work together to make the world better in the knowledge-driven way. Our focus is to minimize the risks, the conflicts and hazards of adapting to intelligent systems in a knowledge-driven environment.

Technological advancements of last few years have produced number of stunning applications and penetrating influences in human life. The prevalence of smartphones, the large-scale implementation of IoT, the use of advanced cloud computing, large-scale machine learning (LLM) and social media, as well as the emergence of powerful artificial intelligence (AI) tools such as deep learning algorithms, are leading to the spread of knowledge that can be used to make analytics-driven decisions and decisions. This large-scale accumulation of information opens the door to the development of knowledge-driven technologies that can have a positive impact on human life and the wider world. This workshop is expected to bring together researchers in the fields of knowledge management and information retrieval, as well as those involved in deep learning, data mining and privacy analytics, to provide insight into the applications and technology that can be leveraged to create human-centric, knowledge-driven systems.

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:

Individuals are encouraged to submit their manuscript in PDF format using the ACM Sigconf template, available at: https://www.acm.org/publications/proceedings-template.The submitted paper should be in two-column Sigconf format. The regular papers should report on significant contributions of lasting value, with a minimum of 7 and a maximum of 9 pages. The regular papers should also include an unlimited number of references. The short/position papers typically discuss new work. The short papers should have a minimum of 4 and a maximum of 6 pages, with an unlimited number of references. 

List of Topics

• Deep learning
• Analytics
• Knowledge Management

Committees

Organizing committee

• Dr. João Gama 
• Dr. Arijit Ukil
• Dr. Leandro Marin
• Dr. Antonio J. Jara

Invited Speakers

• Moshe Y. Vardi, Professor in Computational Engineering at Rice University, ACM Fellow

Venue

University of Birmingham, UK

Contact

kdahcikm@gmail.com