Supervised Semantic Indexing [chapter]

Bing Bai, Jason Weston, Ronan Collobert, David Grangier
2009 Lecture Notes in Computer Science  
We present a class of models that are discriminatively trained to directly map from the word content in a query-document or documentdocument pair to a ranking score. Like Latent Semantic Indexing (LSI), our models take account of correlations between words (synonymy, polysemy). However, unlike LSI our models are trained with a supervised signal directly on the task of interest, which we argue is the reason for our superior results. We provide an empirical study on Wikipedia documents, using the
more » ... links to define document-document or query-document pairs, where we obtain state-of-the-art performance using our method.
doi:10.1007/978-3-642-00958-7_81 fatcat:ixjpdfiehnejjonvnzclshj76y