Exhaustivity
According to WordNet 2 the adjective "exhaustive" means through or thoroughgoing (very thorough; exhaustively complete) "an exhaustive study"; "made a thorough search"; "thoroughgoing research"

In classification it is often demanded that classes should be collectively exhaustive (sometimes thought of as covering the whole universe of knowledge) and mutually exclusive, meaning that any item should have a place in the system and that there is no overlapping between classes. This principle is also known from probability theory:

Exhaustivity is also known in classification and indexing theory and in information retrieval.

Major and minor descriptors are examples on how some databases applies different levels of indexing exhaustivity.
 

"Traditionally the two most important factors governing the effectiveness of an index language have been thought to be the exhaustivity of indexing and the specificity of the index language. There has been much debate about the exact meaning of these two terms. Not wishing to enter into this controversy I shall follow Keen and Digger[1972] in giving a working definition of each.

    For any document, indexing exhaustivity is defined as the number of different topics indexed, and the index language specificity is the ability of the index language to describe topics precisely. Keen and Digger further define indexing specificity as the level of precision with which a document is actually indexed. It is very difficult to quantify these factors. Human indexers are able to rank their indexing approximately in order of increasing exhaustivity or specificity. However, the same is not easily done for automatic indexing.

    It is of some importance to be able to quantify the notions of indexing exhaustivity and specificity because of the predictable effect they have on retrieval effectiveness. It has been recognized (Lancaster[1968]) that a high level of exhaustivity of indexing leads to high recall* and low precision*. Conversely, a low level of exhaustivity leads to low recall and high precision. The converse is true for levels of indexing specificity, high specificity leads to high precision and low recall, etc. It would seem, therefore, that there is an optimum level of indexing exhaustivity and specificity for a given user population.

    Quite a few people (Sparck Jones[1972, 1973], Salton and Yang[1973]), have attempted to relate these two factors to document collection statistics. For example, exhaustivity can be assumed to be related to the number of index terms assigned to a given document, and specificity related to the number of documents to which a given term is assigned in a given collection" (van Rijsbergen, 1979, p. 24-25)

Literature:

Keen, E. M. & Digger, J. A. (1972). Report of an Information Science Index Languages Test. Aberystwyth College of Librarianship, Wales.

Lancaster, F. W. (1968). Information Retrieval Systems: Characteristics, Testing and Evaluation. New York: Wiley.

Salton, G. & Yang, C. S. (1973). On the specification of term values in automatic indexing. Journal of Documentation, 29, 351-372.

Sparck Jones, K. (1972). A statistical interpretation of term specificity and its application in retrieval, Journal of Documentation, 28, 111-21. 

Sparck Jones, K. (1973). Does Indexing Exhaustivity Matter? Journal of the American Society for Information Science, 24(5), 313-316.
 

van Rijsbergen, C. J. (1979). Information Retrieval. 2. ed. London: Butterworths. Online edition 1999.  http://www.dcs.gla.ac.uk/~iain/keith/

Wellish, H. H. (1995). Indexing from A to Z. 2nd edition. New York: H. W. Wilson. (Exhaustivity pp. 175-180).

Wikipedia. The free encyclopedia. (2005). Collectively exhaustive. http://en.wikipedia.org/wiki/Collectively_exhaustive

Birger Hjørland

Last edited: 01-08-2006

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