Taxonomies of concepts are important across many application domains, for instance online shopping portals use catalogs to help users navigate and search for products. Task-dependent taxonomies, e.g., adapting the taxonomy to a specific cohort of users, can greatly improve the effectiveness of navigation and search. However, taxonomies are usually created by domain experts and hence designing t...

Error analysis is a means to assess machine translation output in qualitative terms, which can be used as a basis for the generation of error profiles for different systems. As for other subjective approaches to evaluation it runs the risk of low inter-annotator agreement, but very often in papers applying error analysis to MT, this aspect is not even discussed. In this paper, we report results...

In Case-Based Reasoning (CBR), taxonomies are often used to model similarities. For complex domains and tasks such taxonomies tend to increase in size making them hard to model and maintain. This especially holds true if a group of people is working on the same taxonomy simultaneously. In this paper, we propose a solution by dividing larger taxonomies into sub-taxonomies, which can be regarded ...

BACKGROUND The role of time management in safe and efficient medicine is important but poorly incorporated into the taxonomies of error in primary care. This paper addresses the lack of time management, presenting a framework integrating five time scales termed 'Tempos' requiring parallel processing by GPs: the disease's tempo (unexpected rapid evolutions, slow reaction to treatment); the offic...

There is a demand for taxonomies to organise large collections of documents into categories for browsing and exploration. This paper examines four existing taxonomies that have been manually created, along with two methods for deriving taxonomies automatically from data items. We use these taxonomies to organise items from a large online cultural heritage collection. We then present two human e...

Taxonomies have been proposed numerous times in the literature in order to encode semantic relationships between classes. Such taxonomies have been used to improve classification results by increasing the statistical efficiency of learning, as similarities between classes can be used to increase the amount of relevant data during training. In this paper, we show how data-derived taxonomies may ...