Measuring the Similarity between Automatically Generated Topics
نویسندگان
چکیده
Previous approaches to the problem of measuring similarity between automatically generated topics have been based on comparison of the topics’ word probability distributions. This paper presents alternative approaches, including ones based on distributional semantics and knowledgebased measures, evaluated by comparison with human judgements. The best performing methods provide reliable estimates of topic similarity comparable with human performance and should be used in preference to the word probability distribution measures used previously.
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