Learning to Rank in XML Information Retrieval: Which Feature Improve the Best?

Abstract

The augmented adoption of XML as the standard format for representing a document structure requires the development of tools to retrieve and rank effectively elements of the XML documents. It’s known that in information retrieval, considering multiple sources of relevance improves information retrieval. In this work some relevance features are defined and used in a learning to rank approach for XML information retrieval. Our aim is to combine theses features to derive good ranking function and show the impact of each feature in the relevance of XML element. Experiments on a large collection from the XML Information Retrieval evaluation campaign (INEX) showed good performance of the approach.