Gordon, M.; Kochen, M.: Recall-precision trade-off : a derivation (1989)
0.00
0.0034326524 = product of:
0.024028566 = sum of:
0.0060537956 = weight(_text_:information in 4160) [ClassicSimilarity], result of:
0.0060537956 = score(doc=4160,freq=2.0), product of:
0.052020688 = queryWeight, product of:
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.029633347 = queryNorm
0.116372846 = fieldWeight in 4160, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
1.7554779 = idf(docFreq=20772, maxDocs=44218)
0.046875 = fieldNorm(doc=4160)
0.01797477 = weight(_text_:retrieval in 4160) [ClassicSimilarity], result of:
0.01797477 = score(doc=4160,freq=2.0), product of:
0.08963835 = queryWeight, product of:
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.029633347 = queryNorm
0.20052543 = fieldWeight in 4160, product of:
1.4142135 = tf(freq=2.0), with freq of:
2.0 = termFreq=2.0
3.024915 = idf(docFreq=5836, maxDocs=44218)
0.046875 = fieldNorm(doc=4160)
0.14285715 = coord(2/14)
- Abstract
- The inexact nature of documnet retrieval gives rise to a fundamental recall precision trade-off: generally, recall improves at the expense of precision, or precision improves at the expense of recall. This trade-off os borne out emipically and has qualitatively intuitive explanations. In this article, we explore this realtionship mathematically to explain it further. We see that the recall-precision trade-off hinges on a declaration in the proportion of relevant documents which are retrieved, successively, over time. Futher we examine several mathematical functions sharing this property and conclude that the equation that best modealls recall as a function of time is a logarhitm of a quadratic function. Our conclusion meets the following requirements: the function we derive predicts non-decreasing recall over time until the last relevant document is retrieved (regardless of the density of relevant documents in the collection) without imposing any artificial restrictions on either what percentage of the collection would need to be examined to achieve perfect recall or what the level of precision would be at that time. Other models examined fail to meet oner or more of these criteria.
- Source
- Journal of the American Society for Information Science. 40(1989) no.3, S.145-151
