A scheme for extracting information from collaborative social interaction tools for personalized educational environments

Amal Al-Abri, Zuhoor Al-Khanjari, Naoufel Kraiem, Yassine Jamoussi

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

6 Citations (Scopus)

Abstract

Personalized e-learning systems are mainly structured based on two basic models: domain model and user model. When considering personalization in a collaborative environment with user-generated content via Web 2.0 technologies, the task of generating the models is very challenging. This paper presents an approach to extract information related to the domain model and user model for the purpose of personalization. The extraction is using chat conversations using different social media tools during collaborative learning as sources for the text analysis. Text mining technique has been incorporated to clean the collected data and extract the required information.

Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Computing, Networking and Informatics, ICCNI 2017
EditorsVictor Olu Matthews, Adewole Adewumi, Sanjay Misr
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781509046423
DOIs
Publication statusPublished - Nov 28 2017
Event2017 IEEE International Conference on Computing, Networking and Informatics, ICCNI 2017 - Lagos, Nigeria
Duration: Oct 29 2017Oct 31 2017

Publication series

NameProceedings of the IEEE International Conference on Computing, Networking and Informatics, ICCNI 2017
Volume2017-January

Other

Other2017 IEEE International Conference on Computing, Networking and Informatics, ICCNI 2017
Country/TerritoryNigeria
CityLagos
Period10/29/1710/31/17

Keywords

  • collaborative learning
  • information extraction
  • natural language processing
  • personalization
  • social interaction
  • text mining

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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