Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.12725/11404
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Schroder, Dietrich | - |
dc.contributor.author | Malik, Aakash | - |
dc.date.accessioned | 2020-11-04T10:23:59Z | - |
dc.date.available | 2020-11-04T10:23:59Z | - |
dc.date.issued | 2017 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.12725/11404 | - |
dc.title | Detecting the disaster event with social media data : a GIS based approach. | - |
dc.barcode | 018493 | - |
dc.pages | vi,56p.,CD-ROM | - |
dc.classno | MG TH-0140 MAL | - |
Appears in Collections: | Thesis (Faculty of Technology_PG) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
MG TH-0140.pdf Restricted Access | 4.81 MB | Adobe PDF | Request a copy | |
MG TH-0140 Summary.pdf | 384.78 kB | Adobe PDF | Preview PDF |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.