Speaker: Anuj Jaiswal
Title: Geographic Contextualization for Accounts of Movement (GeoCAM)

Abstract:

Qualitative geographic references in text corpora from field reports,
audio transcriptions, human generated route directions, weblogs, and
other sources provide potentially important information about movement
of entities (people, vehicles, weapons, etc) and about their
underlying spatial behaviors. These qualitative geographic references
can only be interpreted if put in appropriate context. Human analysts
are often able to interpret even vague and imprecise geographic
references by inferring the correct context. However, there are orders
of magnitude more potentially relevant text sources than there are
analysts available to extract the explicit and implicit geographic
references manually. While progress has been made on geographic
information retrieval from text, the progress has been relatively slow
and has focused primarily on extracting and disambiguating place
names.

In this talk, I will present the GeoCAM project which focuses on
algorithms to extract and interpret movement references, then match
these to existing geographic data in order to generate visual
representations on maps. To achieve these goals, we use a
comprehensive and integrated approach in which information contained
in geographic databases and other sources is used iteratively together
with natural language processing methods to interpret geographic
references in context. I will also outline some of the various issues
we encountered while achieving these goals that will highlight the
complexity of this problem.