Related fields

Statistical Semantics focuses on the meanings of common words and the relations between common words, unlike Text Mining, which tends to focus on whole documents, document collections, or named entities (names of people, places, and organizations). Statistical Semantics is a subfield of Computational linguistics and Natural language processing.

Many of the applications of Statistical Semantics (listed above) can also be addressed by lexicon-based algorithms, instead of the corpus-based algorithms of Statistical Semantics. One advantage of corpus-based algorithms is that they are typically not as labour-intensive as lexicon-based algorithms. Another advantage is that they are usually easier to adapt to new languages than lexicon-based algorithms. However, the best performance on an application is often achieved by combining the two approaches (Turney et al., 2003).
References

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