Advanced Techniques in Knowledge Discovery and Data Mining
This explosion is a result of the growing use of electronic media. But what is data mining (DM)? A Web search using the Google search engine retrieves many (really many) definitions of data mining. We include here a few interesting ones. One of the simpler definitions is: “As the term suggests, data mining is the analysis of data to establish relationships and identify patterns” [1]. It focuses on identifying relations in data. Our next example is more elaborate: An information extraction activity whose goal is to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis .
كتب مشابهة
AI in drug discovery
Constitutes the refereed proceedings of the First international workshop on ai in Drug Discovery, AIDD 2024, held as a part of the 33rd International Conference on Artificial Neural Networks, ICANN 2024, in Lugano, Switzerland, on September 19, 2024. These papers focus on various aspects of the rapidly evolving field of Artificial Intelligence (AI)-driven drug discovery in chemistry, including Big Data and advanced Machine Learning, eXplainable AI (XAI), Chemoinformatics, Use of deep learning to predict molecular properties, Modeling and prediction of chemical reaction data and Generative models.
AI in clinical practice : A guide to artificial intelligence and digital medicine
Explains how artificial intelligence is applied to medicine, illustrating not only its enormous potential but also ancillary issues and the limits and risks inherent in its use on a large scale. The book focuses on the intersection between medicine and AI and its implications on the impact of human health care delivery. Topics discussed include wearable devices, health data, Internet of Things, virtual reality, robotic assistance system, and digital intelligence in the health sector. Additionally, sections discuss diagnostics and decision-making systems and machine/deep learning in clinical setting.
Machine learning for cyber-physical systems: selected papers from the international conference ML4CPS 2023
Contains selected papers from the international conference ML4CPS – Machine Learning for Cyber-Physical Systems, which was held in Hamburg (Germany), from 29 to 31 March 2023. Cyber-physical systems are adaptive and learning: they analyze their environment and, based on observations, learn patterns, associations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnostics. Machine learning is the key technology for these developments.
Communication research into the digital society : Fundamental insights from the Amsterdam School of Communication Research
Media and communication have become ubiquitous in today’s societies andaffect all aspects of life. On an individual level, they impact how we learnabout the world, how we entertain ourselves, and how we interact withothers. On an organisational level, the interactions between media andorganisations, such as political parties, NGOs, businesses and brands, shapeorganisations’ reputation, legitimacy, trust and (financial) performance, aswell as individuals’ consumer, political, social and health behaviours. Atthe societal level, media and communication are crucial for shaping publicopinion on current issues such as climate change, sustainability, diversity,and well-being.
