Abstract:
Nowadays, online video platforms mostly recommend related videos by analyzing user-driven data such as viewing patterns, rather than the content of the videos. However, c...Show MoreMetadata
Abstract:
Nowadays, online video platforms mostly recommend related videos by analyzing user-driven data such as viewing patterns, rather than the content of the videos. However, content is more important than any other element when videos aim to deliver knowledge. Therefore, we have developed a web application which recommends related TED lecture videos to the users, considering the content of the videos from the transcripts. TED Talk Recommender constructs a network for recommending videos that are similar content-wise and providing a user interface. Our demo system is available at http://dmserver6.kaist.ac.kr:24673/.
Published in: 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
Date of Conference: 28-31 August 2018
Date Added to IEEE Xplore: 25 October 2018
ISBN Information:
ISSN Information:
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