Linking and Maintaining Quality of Data about MOOCs Using Semantic Computing

Chinmay Dhekne, Srividya Bansal

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

3 Scopus citations

Abstract

Emergence of Linked Data has made it possible to make sense of huge data that is scattered all over the web, and link data from multiple heterogeneous sources. This leads to the challenge of maintaining the quality and integrity of Linked Data, i.e., ensuring outdated data is removed and latest data is included. The focus of this paper is devising strategies to effectively integrate data from multiple sources, publish it as Linked Data, and maintain the quality of Linked Data. The domain used in the study is online education. We present the integration of data from various MOOC providers and algorithms for incrementally updating linked data to maintain their quality in order to constantly keep the users engaged with up-to-date data. Experimental results of the evaluation of the algorithms are presented.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE 11th International Conference on Semantic Computing, ICSC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages81-84
Number of pages4
ISBN (Electronic)9781509048960
DOIs
StatePublished - Mar 29 2017
Event11th IEEE International Conference on Semantic Computing, ICSC 2017 - San Diego, United States
Duration: Jan 30 2017Feb 1 2017

Other

Other11th IEEE International Conference on Semantic Computing, ICSC 2017
CountryUnited States
CitySan Diego
Period1/30/172/1/17

Keywords

  • Data quality
  • Ontology design
  • Semantic querying
  • Semantic web

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Computer Networks and Communications

Fingerprint Dive into the research topics of 'Linking and Maintaining Quality of Data about MOOCs Using Semantic Computing'. Together they form a unique fingerprint.

Cite this