TUM Library

Digital Marketing and Analysis Techniques: Transforming Internet Usage / Meenakshi Sharma, Nidhika Chauhan, Himani Bansal, and Loredana Stanciu -- Machine Learning Techniques and Tools: Merits and Demerits -- V. Ramasamy, B. Gomathy, O. Obulesu, Joy Lal Sarkar, Chhabi Rani Panigrahi, Bibudhendu Pati, and Abhishek Majumder -- Machine Learning and Its Applicability in Networking / Amit Jain and Anand Nayyar -- Machine Learning to Gain Novel Insight on Web Network Analysis / Meenakshi Sharma, Anshul Garg, and Nitin Jain -- Online Trust Evaluation / Deepak Kumar Sharma, Nikita Chawla, and Ravin Kaur Anand -- Trust-Based Sentimental Analysis and Online Trust Evaluation / S. Rakeshkumar and S. Muthuramalingam -- Denaturing the Internet Through a Trust Appraisement Paradigm by QoS Accretion / Sherin Zafar and Deepa Mehta -- Collaborative Filtering in Recommender Systems: Technicalities, Challenges, Applications, and Research Trends / Pradeep Kumar Singh, Pijush Kanti Dutta Pramanik, and Prasenjit Choudhury -- Business Application Analytics Through the Internet of Things / Deepak Kumar Sharma, Pragi Malhotra, and Jayant Verma -- Business Application Analytics and the Internet of Things: The Connecting Link / Ankita Gupta, Ankit Srivastava, Rohit Anand, and Tina Tomažič -- An Enablement Platform for an Internet of Things Application: A Business Model / B.D. Deebak -- Social Media Analytics Using R Programming / Sonia Saini, Ruchika Bathla, and Ritu Punhani.

"This comprehensive and timely book, New Age Analytics: Transforming the Internet through Machine Learning, IoT, and Trust Modeling, explores the importance of tools and techniques used in machine learning, big data mining, and more. The book explains how advancements in the world of the web have been achieved and how the experiences of users can be analyzed. It looks at data gathering by the various electronic means and explores techniques for analysis and management, how to manage voluminous data, user responses, and more. Connectivity through hyperlinks for safe shopping is one of the key areas touched upon in the volume. Modeling for online shopping is also discussed, as is the concept of Quality of Service (QoS) for internet safety, which points to the limits and value of information sharing. Recommender systems with collaborative filtration and an IoT framework along with various payback models are discussed and illustrated with the help of case studies. Also discussed is a plan to gauge the frequency for data evaluation. The relationship between the problem-solving business and the purchaser is also highlighted, showing the importance of the data sets that give information and business analysis using big data. Key features: discusses the tools and techniques used in machine learning; describes the sound principles of big data mining; discusses the rudimentary principles of the social pursuit and connectivity with the humans; considers how online shopping is entangled with networking with social sites and users' experiences; discusses Quality of Service (QoS) and explains the various attacks on cyber, enumerating the ways to enhance the trust in cyber world; looks at the consequences of the recommender system, which is a technique based on collaborative filtering, showing new techniques for e-commerce, discusses the different frameworks of business models of IOT with the help of a case study "-- Provided by publisher.

OCLC-licensed vendor bibliographic record.