We explored the task of creating a textual summary describing a large set of objects characterised by a small number of features using an e-commerce dataset. When a set of consumer products is large and varied, it can be difficult for a consumer to understand how the products in the set differ; consequently, it can be challenging to choose the most suitable product from the set. To assist consumers, we generated high-level summaries of product sets. Two generation algorithms are presented, discussed, and evaluated with human users. Our evaluation results suggest a positive contribution to consumers’ understanding of the domain.
|Title of host publication||Proceedings of the 11th International Conference on Natural Language Generation|
|Number of pages||5|
|Publication status||Published - Nov 2018|
|Event||11th International Conference on Natural Language Generation (INLG 2018) - Tilburg University, Tilburg, Netherlands|
Duration: 5 Nov 2018 → 8 Nov 2018
|Conference||11th International Conference on Natural Language Generation (INLG 2018)|
|Period||5/11/18 → 8/11/18|