Accession Number:

ADA595532

Title:

Geo-Coding for the Mapping of Documents and Social Media Messages

Descriptive Note:

Final rept. 23 Aug 2012-22 May 2013

Corporate Author:

CARNEGIE-MELLON UNIV PITTSBURGH PA OFFICE OF SPONSORED RESEARCH

Personal Author(s):

Report Date:

2013-08-22

Pagination or Media Count:

11.0

Abstract:

Many places on the earth have the same name, so it is difficult to determine which written place is meant. This research aims to improve the precision of geo-coding by using natural language processing and machine learning techniques SVM specifically. We used data that was already geo-coded the ACE Spatial ML data set, and a large tweet set in which tweets were selected for having GPS locations that we could use to improve validity. The report details our methods for text and microtext.

Subject Categories:

  • Information Science
  • Geography
  • Computer Systems

Distribution Statement:

APPROVED FOR PUBLIC RELEASE