Projects per year
Chat conversations between more than two participants are often used in Computer Supported Collaborative Learning (CSCL) scenarios because they enhance collaborative knowledge sharing and sustain creativity. However, multi-participant chats are more difficult to follow and analyze due to the complex ways in which different discussion threads and topics can interact. This paper introduces a novel method based on neural networks for detecting implicit links that uses features computed with string kernels and word embeddings. In contrast to previous experiments with an accuracy of 33%, we obtained a considerable increase to 44% for the same dataset. Our method represents an alternative to more complex deep neural networks that cannot be properly used due to overfitting on limited training data.
|Title of host publication||Artificial Intelligence in Education|
|Subtitle of host publication||19th International Conference, AIED 2018, London, UK, June 27–30, 2018, Proceedings, Part II|
|Editors||C.P. Rosé, R. Martínez-Maldonado, H.U. Hoppe, R. Luckin, M. Mavrikis, K. Porayska-Pomsta, B. McLaren, B. d. Boulay|
|Place of Publication||Cham|
|Number of pages||5|
|Publication status||Published - Jun 2018|
|Event||Artificial Intelligence in Education: 19th International Conference, AIED 2018, London, UK, June 27 – 20, 2018 - London, United Kingdom|
Duration: 27 Jun 2018 → 30 Jun 2018
|Series||Lecture Notes in Computer Science|
|Conference||Artificial Intelligence in Education|
|Abbreviated title||AIED 2018|
|Period||27/06/18 → 30/06/18|
- Computer Supported Collaborative Learning
- Natural Language Processing
- String kernels
- Neural networks
- Implicit links
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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