1 / 7

Ontological Distance Based on Spatial Point Patterns

Ontological Distance Based on Spatial Point Patterns. Ray Dos Santos – Mar 24, 2013. Mapping to an ontology. A fisherman suffered an accident when his boat broke in Anchorage. C. A. VEHICLE. boat. PEOPLE_BY_VOCATION. truck. B. police_officer. CATASTROPHE. clerk. plane. fisherman.

kamran
Download Presentation

Ontological Distance Based on Spatial Point Patterns

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Ontological Distance Based on Spatial Point Patterns Ray Dos Santos – Mar 24, 2013

  2. Mapping to an ontology A fisherman suffered an accident when his boat broke in Anchorage. C A VEHICLE boat PEOPLE_BY_VOCATION truck B police_officer CATASTROPHE clerk plane fisherman train tragedy crash car mishap casualty accident There were 1.2 million car mishaps reported by the police of Fairbanks.

  3. Related Works S(XK,YK) Frequency, probability

  4. Ripley’s K • Ripley’s K function: expected number of events within distance d of an event, divided by mean intensity in the study area crash accident λ 1 λ λ sum of number of objects with attributes i and j that fall within distance d λ = # points / area

  5. N(1m) Ripley’s K 2 3 2 1 d=1m 2 1 0 2 1 2 5m 16 E(N) = 16 / 10 = 1.6 λ = 10 / 25= 0.4 K(1) = 1.6 / 0.4 = 4 5m 4 λ 1 1 λ λ

  6. Conclusion B A fisherman suffered an accident when his boat broke in SF Bay. source 1 CATASTROPHE Last year there were 1.2 million car crashes reported by police in downtown SF. source 2 4 tragedy crash mishap casualty accident dist(crash,accident) = 4 • must also compute: • dist(crash,tragedy) • dist(crash,casualty) • dist(tragedy,mishap) • dist(tragedy,accident) … sim(source1,source2) = sim(crash,accident) + sim(boat,car) + sim(fisherman,police)

  7. Conclusion Ripley’s K function allows scaling: 0 to 5m, 0 to 10m, 0 to 100m, … PCR: pair correlation function per segment: 0 to 5m, 5m to 10m, …

More Related