87 research outputs found
Towards a Trust-based Recommender for Social platforms
No full textFazeli, S., Drachsler, H., & Sloep, P. B. (2013, 19 June). Towards a Trust-based
Recommender for Social platforms. Presented in CWI (Centrum Wiskunde en Informatica), Amsterdam, The Netherlands.The presentation was given in a seminar session in IA group, CWI (Centrum Wiskunde en Informatica), June 19th.EU FP7 Open Discovery Space, NELL
Socio-semantic Networks of Research Publications in the Learning Analytics Community
No full textFazeli, S., Drachsler, H., & Sloep, P. B. (2013). Socio-semantic Networks of Research Publications in the Learning Analytics Community. In M. d'Aquin, S. Dietze, H. Drachsler, E. Herder, & D. Taibi (Eds.), Linked data challenge, Learning Analytic and Knowledge (LAK13) (pp. 6-10). Vol. 974, Leuven, Belgium.In this paper, we present network visualizations and an analysis of publications data from the LAK (Learning Analytics and Knowledge) in 2011 and 2012, and the special edition on Learning and Knowledge Analytics in Journal of Educational Technology and Society (JETS) in 2012.NELLL, FP7 EU Open Discovery Space (ODS
Data-driven study: augmenting predication accuracy of recommendations in social learning platforms
No full textFazeli, S., Drachsler, H., & Sloep, P. B. (2013, 7-8 November). Data-driven study: augmenting predication accuracy of recommendations in social learning platforms. Presented in the 25th Benelux Conference on Artificial Intelligence (BNAIC 2013), Delft, The Netherlands.This study aims to develop a recommender system for a social learning platform to be provided by EU FP7 Open Discovery Space (ODS) project by taking into account social data of users to make recommendations. In this paper, we investigate which recommender algorithm can best fits social learning platforms like ODS platform. We conducted an experiment to test a set of different classical collaborative filtering algorithms on representative educational datasets similar to the future ODS dataset, as well as on the MovieLens dataset as a reference for studies on recommender systems. In addition to the classical collaborative filtering algorithms, we evaluated a graph-based recommender approach called T-index. We compare performance of the used algorithms in terms of F1 score. We also show how T-index approach can provide a balanced distribution of users’ degree centrality.EU FP7 Open Discovery Spac
Towards a Social Trust-aware Recommender for Teachers
No full textFazeli, S., Drachsler, H., Brouns, F., & Sloep, P. B. (2014). Towards a Social Trust-aware Recommender for Teachers. In N. Manouselis, H. Drachsler, K. Verbert & O. C. Santos (Eds.), Recommender Systems for Technology Enhanced Learning (pp. 177-194): Springer New York.Online communities and networked learning provide teachers with social learning opportunities, allowing them to interact and collaborate with others in order to develop their personal and professional skills. However, with the large number of learning resources produced everyday, teachers need to find out what are the most suitable ones for them. In this paper, we introduce recommender systems as a potential solution to this . The setting is the Open Discovery Space (ODS) project. Unfortunately, due to the sparsity of the educational datasets most educational recommender systems cannot make accurate recommendations. To overcome this problem, we propose to enhance a trust-based recommender algorithm with social data obtained from monitoring the activities of teachers within the ODS platform. In this article, we outline the re-quirements of the ODS recommender system based on experiences reported in related TEL recommender system studies. In addition, we provide empirical ev-idence from a survey study with stakeholders of the ODS project to support the requirements identified from a literature study. Finally, we present an agenda for further research intended to find out which recommender system should ul-timately be deployed in the ODS platform.NELLL, EU 7th framework Open Discovery Spac
A Snapshot of Different Types of Under Research Vaccines Against COVID-19: A Review
No full textSARS-CoV-2 as an emerging coronavirus, which first emerged in late 2019 in China causes a respiratory disease called “Coronavirus Disease 2019 (COVID-19)’’. SARS-CoV-2 has since infected more than 26 million people worldwide and caused more than 864000 deaths as of September 04, 2020. The SARS-CoV-2 spike (S) protein consists of two subunits: S1 and S2, which plays a role in binding to cellular receptors and mediating the fusion process between the membranes of the virus and host cells. The S protein has an important role to induce neutralizing-antibody, as well as protective immunity, during SARS-CoV-2 infection. In this review, we focused on different types of the vaccine against COVID-19.
*Corresponding Author: Maryam Fazeli; Email: [email protected]
Please cite this article as: Zandi M, Rashid S, Nasimzade S, Pourhossein B, Fazeli M. A Snapshot of Different Types of Under Research Vaccines Against COVID-19: A Review. Arch Med Lab Sci. 2020;6:1-7 (e7). https://doi.org/10.22037/amls.v6.3237
A trust-based social recommender for teachers
No full textFazeli, S., Drachsler, H., Brouns, F., & Sloep, P. B. (2012). A trust-based social recommender for teachers. In N. Manouselis, H. Drachsler, K. Verbert, & O. C. Santos (Eds.), 2nd Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL 2012) in conjunction with the 7th European Conference on Technology Enhanced Learning (EC-TEL 2012) (pp. 49-60). September, 18-19, 2012, Saarbrücken, Germany.Online communities and networked learning provide teachers with social learning opportunities to interact and collaborate with others in order to develop their personal and professional skills. In this paper, Learning Networks are presented as an open infrastructure to provide teachers with such learning opportunities. However, with the large number of learning resources produced everyday, teachers need to find out what are the most suitable resources for them. In this paper, recommender systems are introduced as a potential solution to address this issue. Unfortunately, most of the educational recommender systems cannot make accurate recommendations due to the sparsity of the educational datasets. To overcome this problem, we propose a research approach that describes how one may take advantage of the social data which are obtained from monitoring the activities of teachers while they are using our social recommender.NELLL, Open Discovery Space (ODS
Lo sviluppo della coscienza morale nella prima infanzia: il contributo di Grazyna Kochanska
No full textPremesse teoriche: La psicologia del ‘900 ha descritto i processi di base dello sviluppo morale. La psicoanalisi, la psicologia cognitiva e quella evoluzionista hanno descritto traiettorie diverse dello sviluppo morale, sottolineando il ruolo delle interazioni e rappresentazioni precoci, della cognizione e del bisogno di connessione interindividuale. Obiettivo: È stata condotta una rassegna sul lavoro di Grazyna Kochanska relativo alle determinanti precoci della Coscienza Morale. Definendo la Coscienza Morale come un sistema autonomo di guida del bambino che si compone di tre sistemi interrelati – emotivo, comportamentale e cognitivo –, le ricerche dell’autrice inseriscono in una cornice sovraordinata i diversi aspetti della moralità infantile descritti dalle principali correnti teoriche del secolo scorso. Metodologia: Abbiamo passato in rassegna alcuni dei contributi più significativi dell’autrice, riportando i dati di maggior rilievo e illustrando quei processi che secondo l’autrice definiscono in modo integrato fasi e peculiarità dello sviluppo precoce di una Coscienza Morale. Discussione critica e conclusioni: Muovendosi all’interno di una cornice integrata, l’autrice descrive l’emergere della Coscienza Morale attraverso l’interdipendenza di emozioni, condotte e cognizione morali sia in relazione al temperamento che alla matrice di accudimento del bambino. In questo modo, la Coscienza Morale in Kochanska diviene un sistema sofisticato ad esordio precoce, che evolve progressivamente durante l’infanzia al fine di guidare il bambino nell’adattare il proprio comportamento in maniera appropriata al suo contesto.Theoretical background: 19th century psychology shed light on child morality and its main processes. Psychoanalysis, cognitive and evolutionary psychology described different moral developmental trajectories during childhood, underlining the part played by early relational interactions and representational processes, the crucial role of cognition, and the need for interindividual connectedness. Objective: Our review focuses on Grazyna Kochanska’s work on the early determinants of Moral Conscience. By describing Moral Conscience as an autonomous inner guiding system which encompasses three interrelated systems – emotional, behavioral and cognitive - Kochanska’s body of research makes it possible to consider within a coherent framework the different aspects peculiar to child’s morality described by the main psychological fields during last century. Method: We reviewed some of Kochanska’s most representative articles, summarizing relevant data and illustrating the processes that in the author’s view tie together phases and peculiarities of an early development of Moral Conscience. Critical discussion and conclusions: Within an integrated framework, the author describes the emergence of a Moral Conscience through the interplay of moral emotions, behaviors and cognitions both in relation to child’s temperament and as shaped by his early caregiving matrix. By so doing, Kochanska see Moral Conscience as a sophisticated system with early onset and evolving through infancy in order to guide the child in adjusting his behavior in a context-appropriate way
Social Trust-Aware Recommendation System: A T-Index Approach
No full textCollaborative Filtering based on similarity suffers from a variety of problems such as sparsity and scalability In this paper, we propose an ontological model of trust between users on a social network to address the limitations of similarity measure in Collaborative Filtering algorithms. For enhancing the constructed network of users based on trust, we introduce an estimate of a user's trustworthiness called T-index to identify and select neighbors in an effective manner We employ T-index to store raters of an item in a so-called TopTrustee list which provides information about users who might not be accessible within a predefined maximum path length. An empirical evaluation shows that our solution improves both prediction accuracy and coverage of recommendations collected along few edges that connect users on a social network by exploiting T-index. We also analyze effect of T-index on structure of trust network to justify the results.</p
A Semantic Trust-based Recommender System using Trust Ontology
No full textThis software provides a recommender system that first creates trust networks of users based on social data of users within a social platform (network) like rating, bookmarking, tagging, commenting, etc. Then, it traverses the trust networks to collect the recommendations for a target user. The output will be also written in OWL files for the purpose of visualisation e.g. with Welkin tool
A Social Recommender System using T-index Approach and Graph Search Mechanism
No full textThe software provides a recommender system, which make recommendations for users in social learning platforms like the one for Open Discovery Space (ODS) projects. The recommender uses user interactions data like rating, bookmarking, commenting, etc. The application has been developed using Java and MySQL. The software is available under GNU Lesser General Public License (LGPL3)
- …
