Scalable Qualitative Representation and Reasoning with Large Spatial Data

發(fā)布時(shí)間：2016-03-13 瀏覽：次

講座題目：Scalable Qualitative Representation and Reasoning with Large Spatial Data

講座人:李三江教授

講座時(shí)間：16:00

講座日期：2016-3-11

地點(diǎn)：長(zhǎng)安校區(qū) 圖書館西附樓報(bào)告廳

主辦單位：計(jì)算機(jī)科學(xué)學(xué)院，圖書館

講座內(nèi)容：Huge volumes of hybrid spatial informationare being capturedfrom sensors and extracted from web documents and socialmedia every day. Ourresearch aims to process massive hybrid spatial informationin an integrativeand efficient way. In this talk, we summarise some of mostrecent progresses,as reported in the following articles:

[1]Long, Z., Li,S. On DistributiveSubalgebras of Qualitative Spatial and Temporal Calculi,Proceedings of the12th Conference on Spatial Information Theory (COSIT 2015),pages 354-374,Santa Fe, New Mexico, USA, October 12-16, 2015.

[2]Long, Z.,Schockaert, S., Li, S.Encoding Large RCC8 Scenarios Using RectangularPseudo-Solutions, Proceedingsof the 15th International Conference on Principlesof Knowledge Representationand Reasoning (KR 2016), Cape Town, South Africa,April 25-29, 2016 (toappear).

[3]Long, Z.,Duckham, M., Li, S.,Schockaert, S. Indexing large geographic datasets withcompact qualitativerepresentation, International Journal of GeographicalInformation Science, 2016(to appear).

[4]Li, S., Long,Z., Liu, W., Duckham, M., Both,A. (2015) On Redundant Topological Constraints.Artificial Intelligence,225:51-76.