'Extract keywords from sentence using TextRank algorithm.
Parameter:
- topK: return how many top keywords. `None` for all possible words.
- withWeight: if True, return a list of (word, weight);
if False, return a list of words.
- allowPOS: the allowed POS list eg. [\'ns\', \'n\', \'vn\', \'v\'].
if the POS of w is not in this list, it will be filtered.
- withFlag: if True, return a list of pair(word, weight) like posseg.cut
if False, return a list of words'

def textrank(self, sentence, topK=20, withWeight=False, allowPOS=(u'ns', u'n', u'vn', u'v'), withFlag=False):

    self.pos_filt = frozenset(allowPOS)
    g = UndirectWeightedGraph()
    cm = defaultdict(int)
    words = tuple(self.tokenizer.cut(sentence))
    for (i, wp) in enumerate(words):
        if self.pairfilter(wp):
            for j in xrange((i + 1), (i + self.span)):
                if (j >= len(words)):
                    break
                if (not self.pairfilter(words[j])):
                    continue
                if (allowPOS and withFlag):
                    cm[(wp, words[j])] += 1
                else:
                    cm[(wp.word, words[j].word)] += 1
    for (terms, w) in cm.items():
        g.addEdge(terms[0], terms[1], w)
    nodes_rank = g.rank()
    if withWeight:
        tags = sorted(nodes_rank.items(), key=itemgetter(1), reverse=True)
    else:
        tags = sorted(nodes_rank, key=nodes_rank.__getitem__, reverse=True)
    if topK:
        return tags[:topK]
    else:
        return tags
