51 participants attended this meeting. As in previous Dagstuhl seminars about Computational Geometry, the exchange of ideas and information about the latest developments in the fields of computational and combinatorial geometry was the main purpose of this meeting. In addition, there was a focus on a few topics on individual days of the meeting, featuring longer keynote talks as well as more te...

Today, we can observe a number of emerging trends in technologies for intelligent knowledge access, including search engines, categorisation tools and visualisation systems. This paper gives a brief overview of them, describes ongoing efforts to develop Semantic Web-based knowledge access tools and discusses how a semantic web-based approach can provide a coherent framework to address many of t...

Despite its explosive growth over the last decade, the Web remains essentially a tool to allow humans to access information. The next generation of the Web, dubbed the ‘Semantic Web’, will extend the Web’s capability through the increased availability machine-processable information. These machine-processable descriptions of Web information resources are called meta-data and are associated with...

Knowledge Management exploded into visibility as a management topic in the mid-1990s with a significant impact in the IT applications area. It has had high visibility for the last decade and, in recent years, has come under some critical scrutiny questioning the success of many of the attempts to manage knowledge, especially those with an IT focus, as well as some suggestion that it was merely ...

This position paper introduces the utility of the conceptual spaces theory to conceptualise the acquired knowledge in data-totext systems. A use case of the proposed method is presented for text generation systems dealing with sensor data. Modelling information in a conceptual space exploits a spatial representation of domain knowledge in order to perceive unexpected observations. This ongoing ...

Question generation (QG) is to generate natural and grammatical questions that can be answered by a specific answer for given context. Previous sequence-to-sequence models suffer from problem asking high-quality requires commonsense knowledge as backgrounds, which in most cases not learned directly training data, resulting unsatisfactory deprived of knowledge. In this paper, we propose multi-ta...

Lack of external knowledge makes empathetic dialogue systems difficult to perceive implicit emotions and learn emotional interactions from limited history. To address the above problems, we propose leverage knowledge, including commonsense lexical explicitly understand express in generation. We first enrich history by jointly interacting with construct an context graph. Then representations kno...