Scientists, researchers and policy makers thus need computational tools to help
them coping with the overwhelming amount of knowledge encoded in text.
One example of these are search engines which retrieve documents matching the
keywords we provide. Search engines are a marvellous technology, but it provides
only a part of the solution. Who has the time to check ten thousand hits for
relevant information? Moreover, search engines often have difficulties with
understanding human language - see Computers and Language.
Text mining aims at processing large amounts of text to reveal hidden
connections and patterns. Since understanding human language is such a hard
task, text mining efforts have focused on extracting predetermined types of
information, ignoring everything else in the text.
For instance, we can focus on identifying all the mentions of marine species in
text. From the observation that two species are frequently mentioned together in
the same sentence, we may deduce that they are probably associated. In addition,
targeting a specific relation between species — like A eats B — would enables us
to automatically construct food chains/webs from text.