Theoretical, Qualitative, and Quantitative Analyses of Small-Document Approaches to Resource Selection

In a distributed retrieval setup, resource selection is the problem of identifying and ranking relevant sources of information for a given user’s query. For better usage of existing resource-selection techniques, it is desirable to know what the fundamental differences between them are and in what settings one is superior to others. However, little is understood still about the actual behavior of resource-selection methods. In this work, we focus on small-document approaches to resource selection that rank and select sources based on the ranking of their documents. We pose a number of research questions and approach them by three types of analyses. First, we present existing small-document techniques in a unified framework and analyze them theoretically. Second, we propose using a qualitative analysis to study the behavior of different small-document approaches. Third, we present a novel experimental methodology to evaluate small-document techniques and to validate the results of the qualitative analysis. This way, we answer the posed research questions and provide insights about small-document methods in general and about each technique in particular.