Which species is it? Species-driven gene name disambiguation using random walks over a mixture of adjacency matrices

Results: Our method performs well in terms of both micro- and macro-averaged performance, achieving micro-F-1 of 0.76 and macro-F-1 of 0.36 on the publicly available DECA corpus. Re-curation of the DECA corpus was performed, with our method achieving 0.88 micro-F-1 and 0.51 macro-F-1. Our method improves over standard classification techniques [such as support vector machines (SVMs)] in a number of ways: flexibility, interpretability and its resistance to the effects of class bias in the training data. Good performance is achieved without the need for computationally expensive parse tree generation or 'bag of words classification'.