Can social information retrieval enhance the discovery and reuse of digital educational content?

Author(s):  
Riina Vuorikari
2019 ◽  
Vol Volume 27 - 2017 - Special... ◽  
Author(s):  
Abir Gorrab ◽  
Ferihane Kboubi ◽  
Henda Ghézala

The explosion of web 2.0 and social networks has created an enormous and rewarding source of information that has motivated researchers in different fields to exploit it. Our work revolves around the issue of access and identification of social information and their use in building a user profile enriched with a social dimension, and operating in a process of personalization and recommendation. We study several approaches of Social IR (Information Retrieval), distinguished by the type of incorporated social information. We also study various social recommendation approaches classified by the type of recommendation. We then present a study of techniques for modeling the social user profile dimension, followed by a critical discussion. Thus, we propose our social recommendation approach integrating an advanced social user profile model. L’explosion du web 2.0 et des réseaux sociaux a crée une source d’information énorme et enrichissante qui a motivé les chercheurs dans différents domaines à l’exploiter. Notre travail s’articule autour de la problématique d’accès et d’identification des informations sociales et leur exploitation dans la construction d’un profil utilisateur enrichi d’une dimension sociale, et son exploitation dans un processus de personnalisation et de recommandation. Nous étudions différentes approches sociales de RI (Recherche d’Information), distinguées par le type d’informations sociales incorporées. Nous étudions également diverses approches de recommandation sociale classées par le type de recommandation. Nous exposons ensuite une étude des techniques de modélisation de la dimension sociale du profil utilisateur, suivie par une discussion critique. Ainsi, nous présentons notre approche de recommandation sociale proposée intégrant un modèle avancé de profil utilisateur social.


Author(s):  
Brendan Luyt ◽  
Chu Keong Lee

In this chapter we discuss some of the social and ethical issues associated with social information retrieval. Using the work of Habermas we argue that social networking is likely to exacerbate already disturbing trends towards the fragmentation of society and a corresponding decline reduction in social diversity. Such a situation is not conducive to developing a healthy, democratic society. Following the tradition of critical theorists of technology, we conclude with a call for responsible and aware technological design with more attention paid to the values embedded in new technological systems.


2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Chahinez Benkoussas ◽  
Patrice Bellot

A combination of multiple information retrieval approaches is proposed for the purpose of book recommendation. In this paper, book recommendation is based on complex user's query. We used different theoretical retrieval models: probabilistic as InL2 (Divergence from Randomness model) and language model and tested their interpolated combination. Graph analysis algorithms such as PageRank have been successful in Web environments. We consider the application of this algorithm in a new retrieval approach to related document network comprised of social links. We called Directed Graph of Documents (DGD) a network constructed with documents and social information provided from each one of them. Specifically, this work tackles the problem of book recommendation in the context of INEX (Initiative for the Evaluation of XML retrieval) Social Book Search track. A series of reranking experiments demonstrate that combining retrieval models yields significant improvements in terms of standard ranked retrieval metrics. These results extend the applicability of link analysis algorithms to different environments.


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