| // Copyright (C) 2012 Davis E. King ([email protected]) | |
| // License: Boost Software License See LICENSE.txt for the full license. | |
| namespace dlib | |
| { | |
| // ---------------------------------------------------------------------------------------- | |
| unsigned long chinese_whispers ( | |
| const std::vector<ordered_sample_pair>& edges, | |
| std::vector<unsigned long>& labels, | |
| const unsigned long num_iterations, | |
| dlib::rand& rnd | |
| ); | |
| /*! | |
| requires | |
| - is_ordered_by_index(edges) == true | |
| ensures | |
| - This function implements the graph clustering algorithm described in the | |
| paper: Chinese Whispers - an Efficient Graph Clustering Algorithm and its | |
| Application to Natural Language Processing Problems by Chris Biemann. | |
| - Interprets edges as a directed graph. That is, it contains the edges on the | |
| said graph and the ordered_sample_pair::distance() values define the edge | |
| weights (larger values indicating a stronger edge connection between the | |
| nodes). If an edge has a distance() value of infinity then it is considered | |
| a "must link" edge. | |
| - returns the number of clusters found. | |
| - #labels.size() == max_index_plus_one(edges) | |
| - for all valid i: | |
| - #labels[i] == the cluster ID of the node with index i in the graph. | |
| - 0 <= #labels[i] < the number of clusters found | |
| (i.e. cluster IDs are assigned contiguously and start at 0) | |
| - Duplicate edges are interpreted as if there had been just one edge with a | |
| distance value equal to the sum of all the duplicate edge's distance values. | |
| - The algorithm performs exactly num_iterations passes over the graph before | |
| terminating. | |
| !*/ | |
| // ---------------------------------------------------------------------------------------- | |
| unsigned long chinese_whispers ( | |
| const std::vector<sample_pair>& edges, | |
| std::vector<unsigned long>& labels, | |
| const unsigned long num_iterations, | |
| dlib::rand& rnd | |
| ); | |
| /*! | |
| ensures | |
| - This function is identical to the above chinese_whispers() routine except | |
| that it operates on a vector of sample_pair objects instead of | |
| ordered_sample_pairs. Therefore, this is simply a convenience routine. In | |
| particular, it is implemented by transforming the given edges into | |
| ordered_sample_pairs and then calling the chinese_whispers() routine defined | |
| above. | |
| !*/ | |
| // ---------------------------------------------------------------------------------------- | |
| unsigned long chinese_whispers ( | |
| const std::vector<ordered_sample_pair>& edges, | |
| std::vector<unsigned long>& labels, | |
| const unsigned long num_iterations = 100 | |
| ); | |
| /*! | |
| requires | |
| - is_ordered_by_index(edges) == true | |
| ensures | |
| - performs: return chinese_whispers(edges, labels, num_iterations, rnd) | |
| where rnd is a default initialized dlib::rand object. | |
| !*/ | |
| // ---------------------------------------------------------------------------------------- | |
| unsigned long chinese_whispers ( | |
| const std::vector<sample_pair>& edges, | |
| std::vector<unsigned long>& labels, | |
| const unsigned long num_iterations = 100 | |
| ); | |
| /*! | |
| ensures | |
| - performs: return chinese_whispers(edges, labels, num_iterations, rnd) | |
| where rnd is a default initialized dlib::rand object. | |
| !*/ | |
| // ---------------------------------------------------------------------------------------- | |
| } | |