Recommender systems have shown to be a successful representative of how data availability can ease our everyday digital life. However, privacy is one the most prominent concerns in era. After several breaches and scandals, users are now worried about sharing their data. In last decade, Federated Learning has emerged as new privacy-preserving distributed machine learning paradigm. It works by pr...

Although feedback from interface agents has recently attracted increasing research attention, most studies emphasize the cognitive influences. Thus, the effect of each feedback type on student perception remains unclear. This study focuses on three types of feedback from interface agents to clarify student perception of single feedback and combinations of feedback types. An empirical study of 4...

Principal aim of a search engine is to provide the sorted results according to user’s requirements. To achieve this aim, it employs ranking methods to rank the web documents based on their significance and relevance to user query. The novelty of this paper is to provide user feedback-based ranking algorithm using reinforcement learning. The proposed algorithm is called RRLUFF, in which the rank...

Trust Establishment is one of the significant resources to enhance the scalability and reliability of resources in the cloud environment. To establish a novel trust model on SaaS (Software as a Service) cloud resources and to optimize the resource utilization of multiple user requests, an integrated software trust estimator with multi-user resource competence (IST-MRC) optimization mechanism is...

Information retrieval systems and their users engage in a dialogue. While the main flow of information is from the system to the user, feedback from the user to the system provides many opportunities for short-term and long-term learning. In this talk, I will explore two interrelated questions that are central to the effective use of feedback. First, how can user feedback be collected so that i...