@inproceedings{jiang-etal-2019-massistant,
title = "{MA}ssistant: A Personal Knowledge Assistant for {MOOC} Learners",
author = "Jiang, Lan and
Hu, Shuhan and
Huang, Mingyu and
Wang, Zhichun and
Yang, Jinjian and
Ye, Xiaoju and
Zheng, Wei",
editor = "Pad{\'o}, Sebastian and
Huang, Ruihong",
booktitle = "Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D19-3023",
doi = "10.18653/v1/D19-3023",
pages = "133--138",
abstract = "Massive Open Online Courses (MOOCs) have developed rapidly and attracted large number of learners. In this work, we present MAssistant system, a personal knowledge assistant for MOOC learners. MAssistant helps users to trace the concepts they have learned in MOOCs, and to build their own concept graphs. There are three key components in MAssistant: (i) a large-scale concept graph built from open data sources, which contains concepts in various domains and relations among them; (ii) a browser extension which interacts with learners when they are watching video lectures, and presents important concepts to them; (iii) a web application allowing users to explore their personal concept graphs, which are built based on their learning activities on MOOCs. MAssistant will facilitate the knowledge management task for MOOC learners, and make the learning on MOOCs easier.",
}
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<abstract>Massive Open Online Courses (MOOCs) have developed rapidly and attracted large number of learners. In this work, we present MAssistant system, a personal knowledge assistant for MOOC learners. MAssistant helps users to trace the concepts they have learned in MOOCs, and to build their own concept graphs. There are three key components in MAssistant: (i) a large-scale concept graph built from open data sources, which contains concepts in various domains and relations among them; (ii) a browser extension which interacts with learners when they are watching video lectures, and presents important concepts to them; (iii) a web application allowing users to explore their personal concept graphs, which are built based on their learning activities on MOOCs. MAssistant will facilitate the knowledge management task for MOOC learners, and make the learning on MOOCs easier.</abstract>
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%0 Conference Proceedings
%T MAssistant: A Personal Knowledge Assistant for MOOC Learners
%A Jiang, Lan
%A Hu, Shuhan
%A Huang, Mingyu
%A Wang, Zhichun
%A Yang, Jinjian
%A Ye, Xiaoju
%A Zheng, Wei
%Y Padó, Sebastian
%Y Huang, Ruihong
%S Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations
%D 2019
%8 November
%I Association for Computational Linguistics
%C Hong Kong, China
%F jiang-etal-2019-massistant
%X Massive Open Online Courses (MOOCs) have developed rapidly and attracted large number of learners. In this work, we present MAssistant system, a personal knowledge assistant for MOOC learners. MAssistant helps users to trace the concepts they have learned in MOOCs, and to build their own concept graphs. There are three key components in MAssistant: (i) a large-scale concept graph built from open data sources, which contains concepts in various domains and relations among them; (ii) a browser extension which interacts with learners when they are watching video lectures, and presents important concepts to them; (iii) a web application allowing users to explore their personal concept graphs, which are built based on their learning activities on MOOCs. MAssistant will facilitate the knowledge management task for MOOC learners, and make the learning on MOOCs easier.
%R 10.18653/v1/D19-3023
%U https://aclanthology.org/D19-3023
%U https://doi.org/10.18653/v1/D19-3023
%P 133-138
Markdown (Informal)
[MAssistant: A Personal Knowledge Assistant for MOOC Learners](https://aclanthology.org/D19-3023) (Jiang et al., EMNLP-IJCNLP 2019)
ACL
- Lan Jiang, Shuhan Hu, Mingyu Huang, Zhichun Wang, Jinjian Yang, Xiaoju Ye, and Wei Zheng. 2019. MAssistant: A Personal Knowledge Assistant for MOOC Learners. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations, pages 133–138, Hong Kong, China. Association for Computational Linguistics.