Abstract

Abstract
By carefully recommending selected items to users, recommender systems ought to increase profit from product sales. To achieve this, recommendations need to be relevant, novel and diverse. Many approaches to this problem exist, each with its own advantages and shortcomings. This paper proposes a novel way to combine model, memory and content-based approaches in a cascade-hybrid system, where each approach refines the previous one, sequentially. It is also proposed a straight-forward way to easily incorporate time-awareness into rating matrices. This approach focuses on being intuitive, flexible, robust, auditable and avoid heavy performance costs, as opposed to black-box fashion approaches. Evaluation metrics such as Novelty Score are also for-malized and computed, in conjunction with Catalog Coverage and mean recommendation price to better capture the recommender's performance.

Abstract
Covid-19 posed several challenges to all organisations in general and to social solidarity cooperatives in particular. However, the challenges faced by these cooperatives have unique features arising from their special characteristics compared to other types of cooperatives. Therefore it is vital to study these challenges and the impacts of covid-19. This study has as main goal to understand those challenges and their impact. An exploratory study was undertaken by applying 11 interviews to 11 social solidarity cooperatives. The cooperatives were chosen to be heterogeneous among the existent cooperatives in Portugal. This study corresponds to the first phase of a project that is still underway. This article presents the main results of the content analysis of the data collected from the interviews. Data show cooperatives could promptly adapt and continue their mission under pressure from the pandemic despite the first difficulties encountered in a new and unknown situation, showing a capacity to adapt and serve their members. However, these members were also submitted to several increasing and new challenges. The adaptations were possible due to legal changes in the work organisation law, from layoff to telework, government support involving financial programs, VAT, and other tax relaxation, as well as due to human resources reorganisation and the cooperatives' staff positive attitude towards the difficulties (both leaders and general workers). Differences between the social solidarity cooperatives under study concerning digital technologies showed that those already having some infrastructure had minor adapting difficulties.

Abstract
The objective of coalition formation is to partition the agent set that gives the highest utility to the system. Over the past three decades, the process of coalition formation has been applied to various real-life applications where agents need to form efficient groups to accomplish a task. This article presents a study of the state-of-the-art approaches on the applications of coalition formation. In particular, it surveys the algorithmic approaches for optimizing the system's welfare. The algorithms are then analyzed based on a framework that consists of two dimensions: (i) the features of the problem environment, which gives an overview of the complexity level of the environment, and (ii) the features of the problem solver, which gives an overview of the solution quality. Our study analyses the approaches in terms of the framework mentioned above, justifies the use of the approaches in a particular problem setting, presents guidance to choose the right algorithmic approach for a problem at hand, and classifies the state-of-the-art approaches according to their basic working principles. This article also presents possible future directions of work to the research community. This study shows that theoretical models need more research before they can be deployed in the real world.

Abstract

Abstract
The use of virtual reality technologies for data visualization and analysis has been an emerging topic of research in the past years. However, one type of data has been left neglected, the point cloud. While some strides have been made in the visualization and analysis of point clouds in immersive environments, these have yet to be used for direct manipulation interactions. It is hypothesized that as with other types of data, bringing direct interactions and 3D visualization to point clouds may increase the ease of performing basic handling tasks. An immersive application for virtual reality HMDs was developed in Unity to help research this hypothesis. It is capable of parsing classified point cloud files with extracted objects and representing them in a virtual environment. Several editing tools were also developed, designed with the HMD controllers in mind. The end result allows the user to perform basic transformative tasks to the point cloud with an ease of use and intuitive feeling unmatched by the traditional desktop-based tools. © 2021 Owner/Author.