A Geometric Model for Information Retrieval Systems

TL;DR

This paper introduces a new geometric linear model to better understand and predict the behavior of information retrieval systems, based on observed patterns in TREC 6 data, with potential applicability to larger datasets.

Contribution

It presents a novel geometric linear model for information retrieval systems, providing a systematic understanding and predictive capability based on empirical data.

Findings

The model accurately predicts relevant documents in TREC 6 data.

The approach is scalable to larger datasets.

The model can be applied to various information retrieval systems.

Abstract

This decade has seen a great deal of progress in the development of information retrieval systems. Unfortunately, we still lack a systematic understanding of the behavior of the systems and their relationship with documents. In this paper we present a completely new approach towards the understanding of the information retrieval systems. Recently, it has been observed that retrieval systems in TREC 6 show some remarkable patterns in retrieving relevant documents. Based on the TREC 6 observations, we introduce a geometric linear model of information retrieval systems. We then apply the model to predict the number of relevant documents by the retrieval systems. The model is also scalable to a much larger data set. Although the model is developed based on the TREC 6 routing test data, I believe it can be readily applicable to other information retrieval systems. In Appendix, we explained a simple and efficient way of making a better system from the existing systems.