A late fusion approach to cross-lingual document re-ranking

The field of information retrieval still strives to develop models which allow semantic information to be integrated in the ranking process to improve performance in comparison to standard bagof-words based models. Cross-lingual information retrieval is an example of where such a model is required, as content or concepts often need to be matched across languages. To overcome this problem, a conceptual model has been adopted in ranking an entire corpus which normally exploits latent/implicit features of the text. One of the drawbacks of this model is that the computational cost is significant and often intractable in modern test collections. Therefore, approaches utilizing conceptbased models for re-ranking initial retrieval results have attracted a considerable amount of study, in particular the latent concept model. However, fitting such a model to a smaller collection is less meaningful than fitting it into the whole corpus. This paper proposes a late fusion method which incorporate...

• Type: Journal
• Year: 2010
• Where: CIKM
• Authors: Dong Zhou, Séamus Lawless, Jinming Min, Vincent Wade
• Keywords: CIKM 2010, Cross-lingual Information Retrieval, Information Retrieval, Information Technology, Model