We explore a meta-indexing scheme that we have called n-term indexing, to solve the collection selection problem. For a given query, a collection selection algorithm should rank a set of known document collections in order of user-relevance. Several selection algorithms employ lexicons that record every unique term from the set of indexed documents: such schemes limit the amount of other inforamtion that may be stored with the indexed terms, and therefore potentially limiting the retrieval effectiveness of the algorithms. An n-term index is a meta-indexign scheme that captures n representative for each document in each collection. Such a scheme may be adapted to suit the characteristics of the federated database, through judicious choice of n. This paper presents issues, results and future plans, relating to our interest in n-term indexing, to solve the collection selection problem.
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