Collocation

In corpus linguistics, a collocation is a sequence of words or terms that co-occur more often than would be expected by chance. In phraseology, collocation is a sub-type of phraseme. An example of a phraseological collocation, as propounded by Michael Halliday, is the expression strong tea. While the same meaning could be conveyed by the roughly equivalent *powerful tea, this expression is considered incorrect by English speakers. Conversely, the corresponding expression for computer, powerful computers is preferred over *strong computers. Phraseological collocations should not be confused with idioms, where meaning is derived, whereas collocations are mostly compositional.

There are about six main types of collocations: adjective+noun, noun+noun (such as collective nouns), verb+noun, adverb+adjective, verbs+prepositional phrase (phrasal verbs), and verb+adverb.

Collocation extraction is a task that extracts collocations automatically from a corpus, using computational linguistics.

Collocation (remote sensing)

Collocation is a procedure used in remote sensing to match measurements from two or more different instruments. This is done for two main reasons: for validation purposes when comparing measurements of the same variable, and to relate measurements of two different variables either for performing retrievals or for prediction. In the second case the data is later fed into some type of statistical inverse method such as a neural network, statistical classification algorithm, kernel estimator or a linear least squares. In principle, most collocation problems can be solved by a nearest neighbor search, but in practice there are many other considerations involved and the best method is highly specific to the particular matching of instruments. Here we deal with some of the most important considerations along with specific examples.

There are at least two main considerations when performing collocations. The first is the sampling pattern of the instrument. Measurements may be dense and regular, such as those from a cross-track scanning satellite instrument. In this case, some form of interpolation may be appropriate. On the other hand, the measurements may be sparse, such as a one-off field campaign designed for some particular validation exercise. The second consideration is the instrument footprint, which can range from something approaching a point measurement such as that of a radiosonde, or it might be several kilometers in diameter such as that of a satellite-mounted, microwave radiometer. In the latter case, it is appropriate to take into account the instrument antenna pattern when making comparisons with another instrument having both a smaller footprint and a denser sampling, that is, several measurements from the one instrument will fit into the footprint of the other.