淘料视频

Dr Kristin Stock is an Associate Profssor of Computer Science and Information Technology and has been Director of the Massey Geoinformatics Collaboratory since 2014. She leads the MBIE Funded project, developing methods to georeference biological collections and the QuakeCoRE funded project, developing methods to map disaster impacts from social media, and was a partner in the MBIE funded project, which developed a Te Ao M膩ori land classification, and the project. 

Kristin completed qualifications in surveying (and is a Registered Surveyor), urban and regional planning and computer science before completing a PhD in semantic database integration at Queensland University of Technology. She has worked as a mining, engineering and cadastral surveyor and for the government, designing a land information system for the Australian Capital Territory, and also ran a successful geospatial data consultancy, Allworlds Geothinking, in the UK for several years. Kristin worked as a Senior Research Fellow at the University of Nottingham in the UK, before moving to 淘料视频 in 2014. 

While in the UK, Kristin worked on a number of large international projects including editing the Protected Sites theme for the Europe-wide ; developing data models for the EU funded and projects (with the British Atmospheric Data Centre); leading research aspects of the JISC funded project and the natural language processing activity in the EU funded project. Kristin collaborates with researchers internationally and has chaired several conferences and workshops.

Kristin is interested in how location is described in natural language (text and spoken language), and in developing automated methods to understand and georeference complex location descriptions such as:

• "we need an ambulance at the far end of the carpark, near the public toilets at Metro Park";
• "the sample was collected on the west bank of the Waikato River, near Hamilton Gardens" or
• "five buildings have collapsed opposite the SkyTower, next to the church".

Kristin works with machine learning, rule-based and knowledge representation methods to address the multiple challenges related to understanding these kinds of expressions, and also works on methods for extracting cultural ecosystem services information from text, as well as cross-linguistic studies of spatial language. She has also worked with ontologies and semantic integration of data from heterogeneous sources, and addresses a range of application areas, including the natural and built environment and disaster management.