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دانلود رایکان مقاله انگلیسی ISI با موضوع الگوریتم مبتنی بر نمونه جهت پیش بینی اتصال در شبکه های زمانی

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الگوریتم مبتنی بر نمونه جهت پیش بینی اتصال در شبکه های زمانی

عنوان انگلیسی مقاله:

Sampling-based algorithm for link prediction in temporal networks

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5. Time complexity analysis

Let n be the number of nodes in the network and L and R be the length and the number of sampled paths, respectively. Obviously, the time complexity for the Generating_Paths algorithm to generate a set of sampled paths is O(R.L). For a given vertex x, the VLP algorithm takes O(R.L) time to compute the similarity terms T’(L, x, y) between x and other vertices in the network. For a temporal network presented by a sequence of time series graphs, line 1 of the TS-VLP algorithm constructs the combined time series graph G1, T in O(n2) time. Line 2 of the algorithm computes the similarity term T’(L, x, y) for each vertex x with other nodes in O(R.L) time. Therefore, it requires O(R.L.n) time to compute the similarity terms for all n nodes in the network. Finally, line3 computes the similarity between all pairs of nodes in O(n2) time. Because R and L can be treated as constants, the time complexity of our proposed algorithm TS-VLP is O(n2). Because there are n2 node pairs in the network, n2 similarity indexes must be computed for the network. Therefore, O(n2) is the lower bound of the time complexity of a similarity-based link prediction algorithm.