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 This leads to the challenge of maintaining the quality and integrity of Linked Data, i.e., ensuring outdated data is removed and latest data is included.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 language | English (US) |
|---|---|
| Title of host publication | Proceedings - IEEE 11th International Conference on Semantic Computing, ICSC 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 81-84 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781509048960 |
| DOIs | |
| State | Published - Mar 29 2017 |
| Event | 11th IEEE International Conference on Semantic Computing, ICSC 2017 - San Diego, United States Duration: Jan 30 2017 → Feb 1 2017 |
Other
| Other | 11th IEEE International Conference on Semantic Computing, ICSC 2017 |
|---|---|
| Country | United States |
| City | San Diego |
| Period | 1/30/17 → 2/1/17 |
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Keywords
- Data quality
- Ontology design
- Semantic querying
- Semantic web
ASJC Scopus subject areas
- Computer Science Applications
- Information Systems
- Computer Networks and Communications
Cite this
Linking and Maintaining Quality of Data about MOOCs Using Semantic Computing. / Dhekne, Chinmay; Bansal, Srividya.
Proceedings - IEEE 11th International Conference on Semantic Computing, ICSC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 81-84 7889510.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Linking and Maintaining Quality of Data about MOOCs Using Semantic Computing
AU - Dhekne, Chinmay
AU - Bansal, Srividya
PY - 2017/3/29
Y1 - 2017/3/29
N2 - 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.
AB - 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.
KW - Data quality
KW - Ontology design
KW - Semantic querying
KW - Semantic web
UR - http://www.scopus.com/inward/record.url?scp=85018326246&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85018326246&partnerID=8YFLogxK
U2 - 10.1109/ICSC.2017.100
DO - 10.1109/ICSC.2017.100
M3 - Conference contribution
SP - 81
EP - 84
BT - Proceedings - IEEE 11th International Conference on Semantic Computing, ICSC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
ER -