Labelling Topics using Unsupervised Graph-based Methods
Νικόλαος Αλέτρας, Mark Stevenson · 2014
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.