Measuring the Similarity between Automatically Generated Topics
Νικόλαος Αλέτρας, Mark Stevenson · 2014
Previous approaches to the problem of measuring similarity between automati-cally generated topics have been based on comparison of the topics ’ word probability distributions. This paper presents alterna-tive approaches, including ones based on distributional semantics and knowledge-based measures, evaluated by compari-son with human judgements. The best performing methods provide reliable esti-mates of topic similarity comparable with human performance and should be used in preference to the word probability distri-bution measures used previously. 1