Automatic query expansion based on tag recommendation
VITOR DUTRA OLIVEIRA, Guilherme C. M. Gomes, Fabiano Muniz Belém, Wladmir Cardoso Brandão, Jussara Marques Almeida, Nívio Ziviani, Marcos André Gonçalves · 2012
We here propose a new method for expanding entity related queries that automatically filters, weights and ranks candidate expasion terms extracted from Wikipedia articles related to the original query. Our method is based on state-of-the-art tag recommendation methods that exploit heuristic metrics to estimate the descriptive capacity of a given term. Originally proposed for the context of tags, we here apply these recommendation methods to weight and rank terms extracted from multiple fields of Wikipedia articles according to their relevance for the article. We evaluate our method comparing it against three state-of-the-art baselines in three collections. Our results indicate that our method outperforms all baselines in all collections, with relative gains in MAP of up to 14% against the best ones.