Unni Cathrine Eiken February 2005

2.2.2 Different types of context
So far, we have argued that using context as a tool to indicate the semantic meaning of a word is
a useful method in linguistics. The method’s theoretical foundation dates back to the middle of
the twentieth century, but has not been pursued much in the last few decades. Even though the
linguistic foundation of this method has been discussed, the advance in computational resources
in recent years has brought this approach forward again. However, this being said, the different
types of context that can be taken into consideration have not been discussed so far in this thesis.
Agreeing on the fact that the semantic meaning of a word is suggested from the linguistic
context in which it occurs, or “the company it keeps”, supports the notion that different words
used in the same context are semantically similar. It does, however, not provide a means for
calculating the degree of this similarity or even finding out exactly which words are similar to
each other. Depending on the information that is desired to obtain about a target word, different
context types mirror different aspects of the semantic meaning of a word. Any approach that
attempts at describing semantic meaning based on the contextual distribution of words in a text
collection must first define the type of context that best will reflect the desirable information.
Somewhat simplified, we distinguish between topical context and local context.
2.2.2.1 Topical context
Topical context (Miller and Leacock 2000), or document context, is a quite wide term that
covers what we could call the “wide conception” of what context is. All other content words
which occur in the same environment as a target word are considered to make up the context of
the word, and following the discussion above, contribute to indicating the semantic meaning of
the target word. A target word’s contextual environment can be further specified depending on
the purpose; in short, the context simply is all the words which occur within a context window
of varying size. The window can be set to cover a certain number of words before and after a
target word, or also to consist of the entire document the target word occurs in. Different
parameters determine the weighting of each word found within the context window; for example
words can be weighted according to their distance from the target word. One extreme way of
looking at topical context might be the bag of words model, where a document is seen as an
unordered collection of words, and the words are weighted by the number of times they occur in
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