Users often search for entities instead of documents and in this setting are willing to provide extra input, in addition to a query, such as category information and example entities. We propose a general probabilistic framework for entity search to evaluate and provide insight in the many ways of using these types of input for query modeling. We focus on the use of category information and show the advantage of a category-based representation over a term-based representation, and also demonstrate the effectiveness of category-based expansion using example entities. Our best performing model shows very competitive performance on the INEX-XER entity ranking and list completion tasks. © 2010 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Balog, K., Bron, M., & De Rijke, M. (2010). Category-based query modeling for entity search. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5993 LNCS, pp. 319–331). Springer Verlag. https://doi.org/10.1007/978-3-642-12275-0_29
Mendeley helps you to discover research relevant for your work.