A knowledge-based method for generating summaries of spatial movement in geographic areas

In this article we describe a method for automatically generating text summaries of data corresponding to traces of spatial movement in geographical areas. The method can help humans to understand large data streams, such as the amounts of GPS data recorded by a variety of sensors in mobile phones, cars, etc. We describe the knowledge representations we designed for our method and the main components of our method for generating the summaries: a discourse planner, an abstraction module and a text generator. We also present evaluation results that show the ability of our method to generate certain types of geospatial and temporal descriptions.

Antarctic climate change and the environment: an update

We present an update of the "key points" from the Antarctic Climate Change and the Environment (ACCE) report that was published by the Scientific Committee on Antarctic Research (SCAR) in 2009. We summarise subsequent advances in knowledge concerning how the climates of the Antarctic and Southern Ocean have changed in the past, how they might change in the future, and examine the associated impacts on the marine and terrestrial biota. We also incorporate relevant material presented by SCAR to the Antarctic Treaty Consultative Meetings, and make use of emerging results that will form part of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report.

A Knowledge-based Approach for Automatic Generation of Summaries of Behavior

Effective automatic summarization usually requires simulating human reasoning such as abstraction or relevance reasoning. In this paper we describe a solution for this type of reasoning in the particular case of surveillance of the behavior of a dynamic system using sensor data. The paper first presents the approach describing the required type of knowledge with a possible representation. This includes knowledge about the system structure, behavior, interpretation and saliency. Then, the paper shows the inference algorithm to produce a summarization tree based on the exploitation of the physical characteristics of the system. The paper illustrates how the method is used in the context of automatic generation of summaries of behavior in an application for basin surveillance in the presence of river floods.