BROAD-RSI \u2013 educational recommender system using social networks interactions and linked data

Crystiam Kelle Pereira,Regina Braga,José Maria N David,Victor Ströele,Fernanda Campos

doi:10.1186/s13174-018-0076-5

Abstract

There are several educational resources distributed in different repositories that address to a wide range of subjects and different educational goals. The proper choice of these educational resources is a challenge. Recommendation systems may help users in this task. In order to generate personalized recommendations, it is important to identify information that will help to define user profile and assist in identifying his/her interests. The constant and ever-increasing use of social networks allows the identification of different information about profile, interests, preferences, style and behavior from the spontaneous interaction. This paper presents an infrastructure able to extract users’ profile and educational context, from the Facebook social network and recommend educational resources. The proposal is supported by Information Extraction Techniques and Semantic Web technologies for extraction, enrichment and definition of user’s profile and interests. The recommendation approach is based on learning objects repositories, linked data and video repositories. It takes advantage of user’s spent time at the web. The proposal evaluation was made from the development of a prototype, three proofs of concept and a case study. The evaluation showed users’ acceptance of extracted information about their educational interests, automatically generated from social network and enriched to find implicit interests. It was also validated the possibility of people recommendation, enabling the establishment of interest network, based on a specific subject, showing good partners to study and research.

Highlights

Easy access to computing devices such as computers, tablets and smartphones, along with the growing use of Internet have brought continuous and fast changes in people’s behavior in relation to access, search and dissemination of information
The main goal of this paper is to propose BROAD-RSI (Recommender System Based on Social Interactions), making possible to extract and exploit information available on social networks to identify features of user’s profile and context, and make individualized and personalized recommendations of educational resources
We must emphasize that we considered educational subjects or interests all those that user wants to know or learn about, not restricted to formal education

Summary

Introduction

Easy access to computing devices such as computers, tablets and smartphones, along with the growing use of Internet have brought continuous and fast changes in people’s behavior in relation to access, search and dissemination of information. This is a multidimensional structural change in people’s life based on information and communication technologies. Some technological tools contribute to educational resources location and selection, such as repositories of Learning Object [1, 2] and Recommender Systems of educational resources [3]. A Recommender System (RS) plays a key role in helping users to find educational resources relevant and pertinent to their profiles and context. It is necessary to identify information that helps user’s profile definition and in identifying requests and interests

Objectives

Results

Conclusion