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In applied probability theory, the Simon model is a class of stochastic models that results in a power-law distribution function. It was proposed by Herbert A. Simon to account for the wide range of empirical distributions following a power-law. It models the dynamics of a system of elements with associated counters (e.g., words and their frequencies in…
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model displaystyle simon power-law network alpha probability nodes growth models dynamics words node gamma class stochastic connectivity new system elements
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Simon model | is a | class of stochastic models that results in a power-law distribution function | 0.90 | text |
| the average path length | instance of | Thus network measures going beyond the degree distribution | 0.80 | text |
| spectral properties | instance of | Thus network measures going beyond the degree distribution | 0.80 | text |
| and clustering coefficient | instance of | Thus network measures going beyond the degree distribution | 0.80 | text |
| cannot be obtained from this mapping.The Simon model is related to generalized scale-free models with growth | instance of | Thus network measures going beyond the degree distribution | 0.80 | text |
| preferential attachment properties | instance of | Thus network measures going beyond the degree distribution | 0.80 | text |
| Simon model | related to Properties | Barabási-Albert | 0.60 | section |
| Simon model | related to Properties | BA | 0.60 | section |
| Simon model | related to Properties | Simon's | 0.60 | section |
| Simon model | related to Properties | In | 0.60 | section |
| Simon model | related to Properties | Simon | 0.60 | section |
| Simon model | related to Properties | Pareto | 0.60 | section |
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