Exploiting User Navigation to Improve Focused Retrieval

Abstract

A common approach for developing XML element retrieval systems is to adapt text retrieval systems to retrieve elements from documents. Two key challenges in this approach are to effectively score structural queries and to control overlap in the output across different search tasks. In this paper, we continue our research into the use of navigation models for element scoring as a way to represent the user’s preferences for the structure of retrieved elements. Our goal is to improve search systems using structural scoring by boosting the score of desirable elements and to post-process results to control XML overlap. This year we participated in the Ad-hoc Focused, Efficiency, and Entity Ranking Tracks, where we focused our attention primarily on the effectiveness of small navigation models. Our experiments involved three modifications to our previous work; (i) using separate summaries for boosting and post-processing, (ii) introducing summaries that are generated from user study data, and (iii) confining our results to using small models. Our results suggest that smaller models can be effective but more work needs to be done to understand the cases where different navigation models may be appropriate.