![]() ![]() Therefore, the time complexity of BSR algorithm is O ( C n d × L ¯ d + C n d × L ¯ d × n ), which could be reduced to O ( C n d × L ¯ d × n ).įurther, we consider the case in which the maximum edit distance is D. Because the time complexity of evaluating the similarity between two n-length service sequences is O( n), the time complexity of the second step is O ( C n d × L ¯ d × n ). In the second step, we have to evaluate the similarity SSim( S 0, S 1) between original service sequence and every candidate service sequence. In the first step, because there are C n d cases while choosing d services from n service, and average L ¯ replaceable services for one service, the time complexity of calculation candidate sequences is O ( C n d × L ¯ d ). Assume that the length of the service sequence is n, and the average number of services that are similar (similarity between services is larger than the minimum similarity Sim min) with one service is L ¯. We first consider the case in which the edit distance is d that is, replace and only replace d services. ![]() As discussed previously, a BSR algorithm consists of two steps: (1) calculating the candidate sequences by replacing and (2) finding out the recommended service sequence.
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