Difference between revisions of "Constructing Learning Maps for Lecture Videos by Exploring Wikipedia Knowledge"

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{{Infobox work
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| title = Constructing Learning Maps for Lecture Videos by Exploring Wikipedia Knowledge
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| date = 2015
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| authors = [[Feng Wang]]<br />[[Xiaoyan Li]]<br />[[Wenqiang Lei]]<br />[[Chen Huang]]<br />[[Min Yin]]<br />[[Ting Chuen Pong]]
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| doi = 10.1007/978-3-319-24075-6_54
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| link = https://link.springer.com/chapter/10.1007/978-3-319-24075-6_54/fulltext.html
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}}
 
'''Constructing Learning Maps for Lecture Videos by Exploring Wikipedia Knowledge''' - scientific work related to [[Wikipedia quality]] published in 2015, written by [[Feng Wang]], [[Xiaoyan Li]], [[Wenqiang Lei]], [[Chen Huang]], [[Min Yin]] and [[Ting Chuen Pong]].
 
'''Constructing Learning Maps for Lecture Videos by Exploring Wikipedia Knowledge''' - scientific work related to [[Wikipedia quality]] published in 2015, written by [[Feng Wang]], [[Xiaoyan Li]], [[Wenqiang Lei]], [[Chen Huang]], [[Min Yin]] and [[Ting Chuen Pong]].
  
 
== Overview ==
 
== Overview ==
 
Videos are commonly used as course materials for e-learning. In most existing systems, the lecture videos are usually presented in a linear manner. Structuring the video corpus has proven an effective way for the learners to conveniently browse the video corpus and design their learning strategies. However, the content analysis of lecture videos is difficult due to the low recognition rate of speech and handwriting texts and the noisy information. In this paper, authors explore the use of external domain knowledge from [[Wikipedia]] to construct learning maps for online learners. First, with the external knowledge, authors filter the noisy texts extracted from videos to form a more precise and elegant representation of the video content. This facilitates us to construct a more accurate video map to represent the domain knowledge of the course. Second, by combining the video information and the external academic articles for the domain concepts, authors construct a directed map to show the relationships between different concepts. This can facilitate online learners to design their learning strategies and search for the target concepts and related videos. Authors experiments demonstrate that external domain knowledge can help organize the lecture video corpus and construct more comprehensive knowledge representations, which improves the learning experience of online learners.
 
Videos are commonly used as course materials for e-learning. In most existing systems, the lecture videos are usually presented in a linear manner. Structuring the video corpus has proven an effective way for the learners to conveniently browse the video corpus and design their learning strategies. However, the content analysis of lecture videos is difficult due to the low recognition rate of speech and handwriting texts and the noisy information. In this paper, authors explore the use of external domain knowledge from [[Wikipedia]] to construct learning maps for online learners. First, with the external knowledge, authors filter the noisy texts extracted from videos to form a more precise and elegant representation of the video content. This facilitates us to construct a more accurate video map to represent the domain knowledge of the course. Second, by combining the video information and the external academic articles for the domain concepts, authors construct a directed map to show the relationships between different concepts. This can facilitate online learners to design their learning strategies and search for the target concepts and related videos. Authors experiments demonstrate that external domain knowledge can help organize the lecture video corpus and construct more comprehensive knowledge representations, which improves the learning experience of online learners.

Revision as of 08:50, 11 August 2019


Constructing Learning Maps for Lecture Videos by Exploring Wikipedia Knowledge
Authors
Feng Wang
Xiaoyan Li
Wenqiang Lei
Chen Huang
Min Yin
Ting Chuen Pong
Publication date
2015
DOI
10.1007/978-3-319-24075-6_54
Links
Original

Constructing Learning Maps for Lecture Videos by Exploring Wikipedia Knowledge - scientific work related to Wikipedia quality published in 2015, written by Feng Wang, Xiaoyan Li, Wenqiang Lei, Chen Huang, Min Yin and Ting Chuen Pong.

Overview

Videos are commonly used as course materials for e-learning. In most existing systems, the lecture videos are usually presented in a linear manner. Structuring the video corpus has proven an effective way for the learners to conveniently browse the video corpus and design their learning strategies. However, the content analysis of lecture videos is difficult due to the low recognition rate of speech and handwriting texts and the noisy information. In this paper, authors explore the use of external domain knowledge from Wikipedia to construct learning maps for online learners. First, with the external knowledge, authors filter the noisy texts extracted from videos to form a more precise and elegant representation of the video content. This facilitates us to construct a more accurate video map to represent the domain knowledge of the course. Second, by combining the video information and the external academic articles for the domain concepts, authors construct a directed map to show the relationships between different concepts. This can facilitate online learners to design their learning strategies and search for the target concepts and related videos. Authors experiments demonstrate that external domain knowledge can help organize the lecture video corpus and construct more comprehensive knowledge representations, which improves the learning experience of online learners.