Aggregation and mapping of social media attribute names extracted from chat conversation for personalized E-learning

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Nowadays learners are using social media applications to perform collaborative learning tasks. Learners from the same class can perform the task through discussions and conversations using different applications. These discussions generate valuable chat conversations contain information related to learners' characteristics. For educators, to understand the personal characteristics of those learners, collecting and analyzing these conversations is required. Due to the varied structure of these applications, an aggregation and mapping mechanism is required. This paper presents an aggregation model for the conversation data collected from different social media applications. This aggregation is built, based on the attributes required to enhance personalization services. The attributes identified have been used to construct a unified format for the chat data generated, using different social web applications. To perform the aggregation task, similarity matching technique using ontology-based model has been adopted. The promising results from the matching process indicate the usefulness of the model.

Original languageEnglish
Title of host publication2019 4th MEC International Conference on Big Data and Smart City, ICBDSC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538680469
DOIs
Publication statusPublished - Feb 19 2019
Event4th MEC International Conference on Big Data and Smart City, ICBDSC 2019 - Muscat, Oman
Duration: Jan 15 2019Jan 16 2019

Publication series

Name2019 4th MEC International Conference on Big Data and Smart City, ICBDSC 2019

Conference

Conference4th MEC International Conference on Big Data and Smart City, ICBDSC 2019
CountryOman
CityMuscat
Period1/15/191/16/19

Keywords

  • Aggregation model
  • Collaborative learning
  • Personalization
  • Semantic mapping
  • Social media

ASJC Scopus subject areas

  • Development
  • Computer Networks and Communications
  • Urban Studies
  • Control and Systems Engineering

Fingerprint Dive into the research topics of 'Aggregation and mapping of social media attribute names extracted from chat conversation for personalized E-learning'. Together they form a unique fingerprint.

Cite this