Text Mining In Educational Research Topic Modeling And Latent Dirichlet Allocation
Download Text Mining In Educational Research Topic Modeling And Latent Dirichlet Allocation PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Text Mining In Educational Research Topic Modeling And Latent Dirichlet Allocation book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Text Mining in Educational Research
This edited book consolidates and documents recent research on topic modeling in text mining using Latent Dirichlet Allocation (LDA). Written by leading experts in topic modeling, it covers a wide range of areas, such as theory building, systematic research, and innovative applications. This book offers a thorough exploration of the latest advancements in topic modeling. From identifying issues in unstructured text data to categorizing documents and extracting valuable insights, the book provides practical use of LDA as a powerful tool in qualitative and quantitative research. The chapters discuss the rapidly evolving landscape of topic modeling algorithms and offer tangible examples and applications of LDA in educational research, showcasing its real-world impact. This book dives into the heart of educational research and uncovers the transformative potential of Latent Dirichlet Allocation in shaping the future of topic modeling. This book is a valuable resource, highlighting exemplary works and rapid advances in the field. It appeals to students, researchers, and practitioners interested in text mining.
R and Data Mining
R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more.Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation.With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis. - Presents an introduction into using R for data mining applications, covering most popular data mining techniques - Provides code examples and data so that readers can easily learn the techniques - Features case studies in real-world applications to help readers apply the techniques in their work
Information Technology and Systems
This book is composed by the papers written in English and accepted for presentation and discussion at The 2023 International Conference on Information Technology & Systems (ICITS'23), held at Universidad Nacional de San Antonio Abad del Cusco, in Cusco, Peru, between the 24th and the 26th of April 2023. ICIST is a global forum for researchers and practitioners to present and discuss recent findings and innovations, current trends, professional experiences and challenges of modern information technology and systems research, together with their technological development and applications. The main topics covered are: information and knowledge management; organizational models and information systems; software and systems modelling; software systems, architectures, applications and tools; multimedia systems and applications; computer networks, mobility and pervasive systems; intelligent and decision support systems; big dataanalytics and applications; human–computer interaction; ethics, computers & security; health informatics; information technologies in education, and Media, Applied Technology and Communication.