KDAH-CIKM is traditionally recognized as a workshop in 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 CIKM for past two years that inculcates the positive social impact in knowledge-driven analytics research. This workshop is intended to demonstrate the capability of knowledge-driven analytics for building human-centric applications using big data and AI focusing on agent-based modelling, machine learning and deep learning, causal model creation, explainable AI, fairness, game theory, planning, neuro-symbolic AI and related others. Knowledge-driven human beings, knowledge-driven societies and knowledge-driven technologies should co-operatively co-exist to create a better knowledge-driven world. 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 ubiquity of smartphones, large scale deployment of Internet of Things, high end cloud computing, LLMs, impactful and gross engagement to social networks along with the advent and promise of powerful artificial intelligent tools like deep learning algorithms result in abundance of information generation, dissemination of knowledge and analytics-driven human decisions and choices. Such conglomeration of technologies, applications and the big data resources paves ways for knowledge-driven human life, society and economy.
The prime objective of this workshop is to bring forward the applications and technologies that through knowledge-driven analytics bring positive outcomes to the human life and to the world at large. For example, knowledge-managed learning techniques have the capability of providing robust prediction of medical condition or epidemic outbreak, minimization of diagnosis error, enabling remote disease screening. It can predict the suicidal trend or state of depression from analysing Facebook posts, tweets or recent posted images. Big data and availability of vast information invite severe data privacy attacks, which can potentially ruin one’s life and reputation. We expect researchers in the field of knowledge management, information retrieval, artificial intelligence, deep learning, reasoning, data mining, privacy analytics will provide insights of technological aspects as well as application-specific scenarios of human-centric knowledge-driven analytics and systems.