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All Outputs (4)

Understanding people's perceptions of their liveable neighbourhoods: A case study of East Bristol (2023)
Conference Proceeding
Covato, E., & Jeawak, S. (2023). Understanding people's perceptions of their liveable neighbourhoods: A case study of East Bristol. . https://doi.org/10.4230/LIPIcs.GIScience.2023.24

Liveable neighbourhoods are urban planning initiatives that aim to improve the quality of residential areas. In this paper, we focus on the East Bristol Liveable Neighbourhood (EBLN) to understand people’s perceptions of their neighbourhood’s urban r... Read More about Understanding people's perceptions of their liveable neighbourhoods: A case study of East Bristol.

A mixture-of-experts model for learning multi-facet entity embeddings (2020)
Conference Proceeding
Alshaikh, R., Bouraoui, Z., Jeawak, S., & Schockaert, S. (2020). A mixture-of-experts model for learning multi-facet entity embeddings. In Proceedings of the 28th International Conference on Computational Linguistics (5124-5135)

Various methods have already been proposed for learning entity embeddings from text descriptions. Such embeddings are commonly used for inferring properties of entities, for recommendation and entity-oriented search, and for injecting background know... Read More about A mixture-of-experts model for learning multi-facet entity embeddings.

Cardiff University at SemEval-2020 Task 6: Fine-tuning BERT for Domain-Specific Definition Classification (2020)
Conference Proceeding
Jeawak, S. S., Espinosa-Anke, L., & Schockaert, S. (2020). Cardiff University at SemEval-2020 Task 6: Fine-tuning BERT for Domain-Specific Definition Classification. In Proceedings of the Fourteenth Workshop on Semantic Evaluation (361-366)

We describe the system submitted to SemEval-2020 Task 6, Subtask 1. The aim of this subtask is to predict whether a given sentence contains a definition or not. Unsurprisingly, we found that strong results can be achieved by fine-tuning a pre-trained... Read More about Cardiff University at SemEval-2020 Task 6: Fine-tuning BERT for Domain-Specific Definition Classification.

Embedding geographic locations for modelling the natural environment using flickr tags and structured data (2019)
Conference Proceeding
Jeawak, S. S., Jones, C. B., & Schockaert, S. (2019). Embedding geographic locations for modelling the natural environment using flickr tags and structured data. In Advances in Information Retrieval. , (51-66). https://doi.org/10.1007/978-3-030-15712-8_4

Meta-data from photo-sharing websites such as Flickr can be used to obtain rich bag-of-words descriptions of geographic locations, which have proven valuable, among others, for modelling and predicting ecological features. One important insight from... Read More about Embedding geographic locations for modelling the natural environment using flickr tags and structured data.