### Introduction

The *term frequency normalisation tuning* estimates the free-parameter of a TermFrequencyNormalisation method. It is a crucial issue in InformationRetrieval that significantly affects robustness and effectiveness of retrieval performance.

### Term frequency normalisation tuning by measuring normalisation effect

The tuning method by measuring normalisation effect estimates the free-parameters of BM25'sNormalisation and the Normalisation2 of the DivergenceFromRandomness models (He & Ounis, ECIR2005). The notion of *normalisation effect* refers to the variation of the term frequency with respect to the DocumentLength distribution, as defined in (He & Ounis, ECIR2005). The *optimal normalisation effect* stands for the normalisation effect measure that corresponding to the parameter setting that gives the highest mean average precision, which is a collection-independent constant. The tuning methodology can be summarised as follows:

Obtain the optimal normalisation effect on a training collection using relevance assessment.

On a given new collection, apply the parameter setting such that it gives the optimal normalisation effect.

On a given new collection, the normalisation effect is computed over a set of queries that are generated by the QuerySimulation based on the DFR model.