Combining Information from Multiple Internet Sources

could interpret it as number of basic operations (in the sense defined above) to unify two different
result sets.
Following example illustrates how the distance between two result sets can be evaluated.
Example:
Let us consider following result sets:
RS1 = (a, b, c)
RS2 = (b, c, a)
Then the distance between those result sets is equal to 2.
To obtain RS2 from RS1 one is required to do:
1 deletion – remove a from the beginning
1 insertion – add a at the end
It gives following 2 alignments:
1. (a, b, c)
(b, c, a)
2. (a, b, c, -)
(-, b, c, a)
What corresponds to lowest cost path from (-1, -1) to (2, 2)
-1 0 1 2
b c A
-1 0 1 2 3
0 a 1 1 2 2
1 b 2 1 2 3
2 c 3 2 1 2
Listing 3.4.3 Example of variation of algorithm for Levenshtein distance
This distance is used in Consensus Method. It is used during the main algorithm part and
also during weights calculation after it. The following listing presents pseudo code of dynamic
programming version of the variation of this algorithm.
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