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Add json file to help standardise parameter descriptions
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{
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"G": "The graph to run the algorithm on.",
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"sudo": "Disable the memory guard.",
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"log_progress": "Display progress logging.",
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"username": "As an administrator, run the algorithm as a different user, to access also their graphs.",
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"job_id": "Identifier for the computation.",
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"tolerance": "Minimum change in scores between iterations.",
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"concurrency": "Number of CPU threads to use.",
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"max_iterations": "Maximum number of iterations to run.",
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"scaler": "Name of the scaler applied on the resulting scores.",
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"source_nodes": "List of node ids to use as starting points. Use a list of list pairs to associate each node with a bias > 0.",
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"orientation": "The orientation of relationships to consider. Can be 'NATURAL', 'REVERSE', or 'UNDIRECTED'.",
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"sampling_size": "Number of source nodes to consider for computing centrality scores.",
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"sampling_seed": "Seed value for the random number generator that selects source nodes.",
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"damping_factor": "Probability of a jump to a random node.",
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"use_wasserman_faust": "Use the improved Wasserman-Faust formula for closeness computation.",
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"seed_set_size": "Number of nodes that maximize the expected spread in the network.",
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"propagation_probability": "Probability of a node being activated by an active neighbour node.",
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"monte_carlo_simulations": "Number of Monte-Carlo simulations.",
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"mutate_property": "Name of the node property to store the results in.",
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"write_property": "Name of the node property to store the results in.",
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"node_labels": "Filter the graph using the given node labels. Nodes with any of the given labels will be included.",
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"relationship_types": "Filter the graph using the given relationship types. Relationships with any of the given types will be included.",
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"relationship_weight_property": "Name of the property to be used as weights.",
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}

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