MSS: Investigating the Effectiveness of Domain Combinations and Topic Features for Word Sense Disambiguation
Sanae Fujita, Kevin Duh, Akinori Fujino, Hirotoshi Taira, Hiroyuki Shindo · 2010
We participated in the SemEval-2010 Japanese Word Sense Disambiguation (WSD) task (Task 16) and focused on the following: (1) investigating domain differences, (2) incorporating topic features, and (3) predicting new unknown senses. We experimented with Support Vector Machines (SVM) and Maximum Entropy (MEM) classifiers. We achieved 80.1 % accuracy in our experiments. 1