Topic Models Can Improve Domain Term Extraction

Elena I. Bolshakova, Natalia V. Loukachevitch, Michael Nokel

Abstract: The paper describes the results of an experimental study of topic models applied to the task of single-word term extraction. The experiments encompass several probabilistic and non-probabilistic topic models and demonstrate that topic information improves the quality of term extraction, as well as NMF with KL-divergence minimization is the best among the models under study.