This topic provides guidelines for tuning the clustering parameters.

The guidelines for the clusters tuning strategy include initial values that are used for the first trial clustering run and recommended values. The tuning process involves changing the parameters from their initial values to their recommended values, with certain variation dependent on the properties of the particular data set and the application needs.

In general, the tuning strategy involves starting with the parameters at a permissive setting and then gradually decreasing the value. You tune the parameters by observing their impact simultaneously on the results for several different queries: no query or node 0, broad queries, narrow queries, single-term query, and multi-term query. In other words, you should avoid tuning the parameters based on a specific query.

The following procedure is intended as a tool for gradual tuning. It allows you to observe the effect of changing the parameters on several different queries at once. Use the suggested order. It maps to the order in which these parameters impact the clustering algorithm, from upstream to downstream.