Chinese Whispers 聚类算法

Chinese Whispers 聚类算法用于当你不知道有多少个类时。他的基本算法步骤是：

1，对于所有节点v，都赋值一个初始的类class（vi）=i

2，随机选取一个节点vt，找到v所有的临接节点，对临接节点所属的类进行打分。例如一个节点1的临接节点有2,3,4,5,分别属于a,b,c,b类别，边1-2,1-3,1-4,1-5的权值都为1，那么类a的得分就是1，类b得分2，类c得分1

3，将得分最高的类别赋值给vt

4，返回2

下面上dlib的代码进行解析：

inline unsigned long chinese_whispers (
const std::vector<ordered_sample_pair>& edges,
std::vector<unsigned long>& labels,
const unsigned long num_iterations,
dlib::rand& rnd
)
{
// make sure requires clause is not broken，传进来的边集需要排好序
DLIB_ASSERT(is_ordered_by_index(edges),
"\t unsigned long chinese_whispers()"
<< "\n\t Invalid inputs were given to this function"
);

labels.clear();
if (edges.size() == 0)
return 0;

std::vector<std::pair<unsigned long, unsigned long> > neighbors;
find_neighbor_ranges(edges, neighbors);

// Initialize the labels, each node gets a different label.
 
labels.resize(neighbors.size());
for (unsigned long i = 0; i < labels.size(); ++i)
labels[i] = i;

for (unsigned long iter = 0; iter < neighbors.size()*num_iterations; ++iter)
{
// Pick a random node.随机挑选一个节点
const unsigned long idx = rnd.get_random_64bit_number()%neighbors.size();

// Count how many times each label happens amongst our neighbors.对节点的临接几点所属的类别进行统计打分
std::map<unsigned long, double> labels_to_counts;
const unsigned long end = neighbors[idx].second;
for (unsigned long i = neighbors[idx].first; i != end; ++i)
{
labels_to_counts[labels[edges[i].index2()]] += edges[i].distance();
}

// find the most common label.找到得分最高的类，并给该节点归类
std::map<unsigned long, double>::iterator i;
double best_score = -std::numeric_limits<double>::infinity();
unsigned long best_label = labels[idx];
for (i = labels_to_counts.begin(); i != labels_to_counts.end(); ++i)
{
if (i->second > best_score)
{
best_score = i->second;
best_label = i->first;
}
}

labels[idx] = best_label;
}

// Remap the labels into a contiguous range. First we find the
// mapping.因为上述找到的类别可能不是连续的0,1,2,3...,需要对类别进行重新映射为连续的编号
std::map<unsigned long,unsigned long> label_remap;
for (unsigned long i = 0; i < labels.size(); ++i)
{
const unsigned long next_id = label_remap.size();
if (label_remap.count(labels[i]) == 0)
label_remap[labels[i]] = next_id;
}
// now apply the mapping to all the labels.给所有节点赋值类别
 for (unsigned long i = 0; i < labels.size(); ++i)
{
labels[i] = label_remap[labels[i]];
}

return label_remap.size();
}相关参考论文
《Chinese Whispers - an Efficient Graph Clustering Algorithm and its Application to Natural Language Processing Problems》