Building an automated text mining algorithm to extract location-based information from online documents

Text documents often include information pertaining to geographic locations. Mapping these place names to specific geographic locations (e.g., GIS) requires a considerable amount of human effort. This becomes challenging especially when the same place name is represented by multiple places, such as in the naming of waterbodies (e.g. lakes and rivers). In this project we will develop an integrated system, bringing together Natural Language Processing, Machine Learning, and one or more known text mining software tools for geographic location application in order to evaluate an online document to match any place names with a geographic location that can be used by GIS. Goldstream Publishing Inc. operates The Angler’s Atlas, which is a sport fishing service that provides detailed maps and related information for lakes and rivers across North America. Providing current information on thousands of the catalogued waterbodies is a challenge for the company.

Faculty Supervisor:

Liang Chen

Student:

Partner:

The Angler's Atlas

Discipline:

Computer science

Sector:

Agriculture

University:

University of Northern British Columbia

Program: