Document length normalization adjusts the term frequency or the relevance score in order to normalize the effect of document length on the document ranking.
The reasons for employing a document length normalization method in an IR system are quite subtle. In general, the effect observed on the ranking by the presence of many lengthy documents in a collection is to favor their retrieval with respect to shorter documents.
Singhal, Buckley and Mitra gave the following two reasons for adopting a length normalization in the vector space model :
The same term usually occurs repeatedly in long documents.
The vocabulary of a long document is usually large.
In 1994, Robertson and Walker also studied the effect of document length in the context of the probabilistic model. They observed that:
Some documents may simply cover more material than others, […], a long document covers a similar scope to a short...
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Amati G. Probabilistic models for information retrieval based on divergence from randomness. Ph.D. Thesis, Department of Computing Science, University of Glasgow, 2003.
Robertson S. E. and Walker S. Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval. In Proc. 17th Annual Int. ACM SIGIR Conf. on Research and Development in Information Retrieval, 1994, pp. 232–241.
Robertson S.E., Walker S., Jones S., and Hancock-Beaulieu M. Okapi at trec-3. In Proc. The 3rd Text Retrieval Conference, 1994.
Singhal A., Buckley C., and Mitra M. Pivoted document length normalization. In Proc. 19th Annual Int. ACM SIGIR Conf. on Research and Development in Information Retrieval, 1996, pp. 21–29.
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He, B. (2009). Document Length Normalization. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_934
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-35544-3
Online ISBN: 978-0-387-39940-9