This book constitutes the refereed proceedings of the 11th International Conference on Distributed Computing and Internet Technology, ICDCIT 2015, held in Bhubaneswar, India, in February 2015. The 12 revised full papers presented together with 30 short papers and 9 invited talks in this volume were carefully reviewed and selected from 221 submissions. The papers cover topics such as distributed computing and algorithms; internet technologies and Web services; secure computing and communication; cloud computing; information retrieval and recommender systems and societal applications.

This book contains the papers presented at the First International Conference on Innovations in Intelligent Computing and Communication, ICIICC 2021, held in Bhubaneswar, Odisha, India, in December, 2022. The 31 full papers presented were thoroughly reviewed and selected from 78 submissions. They are divided in three tracks with the following topics: Intelligent Computing; Communications; and Machine Learning and Data Analytics.

Although recommendation systems have become a vital research area in the fields of cognitive science, approximation theory, information retrieval and management sciences, they still require improvements to make recommendation methods more effective and intelligent. Intelligent Techniques in Recommendation Systems: Contextual Advancements and New Methods is a comprehensive collection of research on the latest advancements of intelligence techniques and their application to recommendation systems and how this could improve this field of study.

Our book includes some state-of-the-art classical and non-classical approaches of data mining and given a well-balanced treatment of both theory and practice. This book is presented in a simple and lucid manner. Many case studies are provided for easy understanding of the readers. Hybrid approaches are new and included in this text. Application to intrusion detection attracts more researchers to this. Recently, Data Mining (DM) algorithms have been successfully applied in IDS in order to uncover new insights, associations and hidden patterns within large data set of logs and messages.