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Hinrich Schütze is a researcher in natural language processing and computational linguistics whose work includes learning representations of language from text. His LMU profile identifies his research and teaching at its Center for Information and Language Processing.^[ref]

In his 1998 paper Automatic Word Sense Discrimination by Hinrich Schütze, occurrences of an ambiguous word are represented by their surrounding context and grouped using clustering. The groups can distinguish uses without requiring a human to supply a sense label for every training example. The paper investigates alternative representations and evaluates how well the resulting groups separate uses.^[ref]

For an illustrative example, occurrences of “bank” near “loan” and “account” differ from occurrences near “river” and “flood”. A context vector can record such differences, and clustering can group similar vectors. This is a problem of discovering useful structure from data; the algorithm's groups need not coincide perfectly with the entries of a human dictionary. The example connects his work to unsupervised learning and to the broader use of word embeddings.