Predicting Relevance Feedback Effectiveness with the Help of the Principle of Polyrepresentation in MIR

Abstract

The principle of polyrepresentation - a representative of the cognitive viewpoint on IR, takes a holistic perspective on interactive IR research. One of the principle's core hypotheses is that a document is described by different representations such as visual low-level features, textual content, or relational metadata. The conjunctive combination of these representations, the so-called cognitive overlap, is assumed to compensate the inherent insecurity in relevance assessments of documents w.r.t. an information need. Recently, the cognitively motivated principle of polyrepresentation has been shown to correlate with quantum mechanics-inspired IR models. However, the principle's effectiveness has not been examined in relevance feedback-based interactive MIR. In this work, the principle's utility is studied in interactive MIR in order to investigate whether its main hypothesis can serve as a predictor of retrieval performance during relevance feedback. In order to obtain resilient results all experiments have been carried out with 6 different standard test sets that provide evidence of the utility of the presented approach and the underlying polyrepresentative hypothesis.