This paper introduces an unsupervised graph-based method that selects textual labels for automatically generated topics. Our approach uses the topic keywords to query a search engine and generate a graph from the words contained in the results. PageRank is then used to weigh the words in the graph and score the candidate labels. The state-of-the-art method for this task is supervised (Lau et al., 2011) . Evaluation on a standard data set shows that the performance of our approach is consistently superior to previously reported methods.
Undirected PageRank algorithm was used to assign weights to words and score candidate labels REF .
Labelling Topics using Unsupervised Graph-based Methods
ACL
Computer Science