转载于http://en.wikipedia.org/wiki/Dice’s_coefficient

出自Wikipedia

Dice’s coefficient, named after Lee Raymond Dice[1] and also known as the Dice coefficient, is a similarity measure related to the Jaccard index.

For sets X and Y of keywords used in information retrieval, the coefficient may be defined as twice the shared information (intersection) over the combined set (union) :[2]

s = \frac{2 | X \cap Y |}{| X | + | Y |}

When taken as a string similarity measure, the coefficient may be calculated for two strings, x and y using bigrams as follows:[3]

s = \frac{2 n_t}{n_x + n_y}

where nt is the number of character bigrams found in both strings, nx is the number of bigrams in string x and ny is the number of bigrams in string y. For example, to calculate the similarity between:

night
nacht

We would find the set of bigrams in each word:

{ni,ig,gh,ht}
{na,ac,ch,ht}

Each set has four elements, and the intersection of these two sets has only one element: ht.

Inserting these numbers into the formula, we calculate, s = (2 · 1) / (4 + 4) = 0.25.

[编辑]See also


The Wikibook Algorithm implementation has a page on the topic of

Dice’s coefficient

[编辑]Notes

  1. ^ Dice, Lee R. (1945). “Measures of the Amount of Ecologic Association Between Species”. Ecology 26 (3): 297–302. doi:10.2307/1932409.
  2. ^ van Rijsbergen, Cornelis Joost (1979). Information Retrieval. London: Butterworths.
  3. ^ Kondrak, Grzegorz; Marcu, Daniel; and Knight, Kevin (2003). “Cognates Can Improve Statistical Translation Models”. Proceedings of HLT-NAACL 2003: Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics. pp. 46–48.

[编辑]References

3个分类: Information retrieval | String similarity measures | Measure theory