Every day new information is available in text, images, sounds, and
other media that are difficult to search with current
technology. Existing text retrieval systems effectively treat
documents as unstructured bags of words. Yet it is clear that human
processors of information make use of a much deeper understanding of
text than these systems exhibit. Humans cannot compete with machines
in terms of quantity, but their abilities far exceed those of machines
when it comes to quality.
This priority research area focuses on how we can improve search
technology by integrating more knowledge about the processing and
understanding of language. This knowledge comes from a range of
disciplines represented within HCSNet. What aspects of natural
language processing are most effective to find information and present
it to the user? How can current linguistics theories help us find
better results? Are there insights from the cognitive sciences that
can tell us how to build better tools for finding information? How do
we extend these technologies when the data we are concerned with
includes images, audio and video as well as text?
Events
