Projects per year
Multi-participant chat conversations are one of the most frequently employed Computer Supported Collaborative Learning tools due to their ease of use. Moreover, chats enhance knowledge sharing, sustain creativity and aid in collaborative problem solving. Nevertheless, the manual analysis of multi-participant chats is a difficult task due to the mixture of different topics and the inter-twinning of multiple discussion threads during the same conversation. Several tools that employ Natural Language Processing techniques have been developed to automatically identify links between contributions in order to facilitate the tracking of topics and of discussion threads, as well as to highlight key contributions in terms of follow-up impact. This paper proposes a novel method for detecting implicit links based on features computed using string kernels and word embeddings, combined with neural networks. This method significantly outperforms previous results on the same dataset. Due to its smaller size, our model represents an alternative to more complex deep neural networks, especially when limited training data is available as is the case of CSCL chats in a specific domain.
|Title of host publication||13th European Conference on Technology Enhanced Learning (EC-TEL 2018)|
|Editors||V. Pammer-Schindler, M. Pérez-Sanagustín, H. Drachsler, R. Elferink, M. Scheffel|
|Publication status||Published - 2018|
|Event||13th European Conference on Technology Enhanced Learning: Lifelong Technology-Enhanced Learning (EC-TEL 2018) - Leeds, United Kingdom|
Duration: 3 Sept 2018 → 6 Sept 2018
|Conference||13th European Conference on Technology Enhanced Learning|
|Abbreviated title||EC-TEL 2018|
|Period||3/09/18 → 6/09/18|
- Computer Supported Collaborative Learning
- Implicit links identification
- Natural Language Processing
- String kernels
- Neural networks
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- 1 Finished
Rage: Realising an Applied Gaming Eco-system
Westera, W., Georgiadis, K., Saveski, G., van Lankveld, G., Bahreini, K., van der Vegt, W., Berkhout, J., Nyamsuren, E., Kluijfhout, E. & Nadolski, R.
1/02/15 → 31/07/19