Apache Solr Reference Guide Covering Apache Solr 6.0

The query issued to the system was Solr. It seems clear that faceting could not yield a similar set of groups,
although the goals of both techniques are similar—to let the user explore the set of search results and either
rephrase the query or narrow the focus to a subset of current documents. Clustering is also similar to Result
Grouping in that it can help to look deeper into search results, beyond the top few hits.
Topics covered in this section:
Preliminary Concepts
Quick Start Example
Installation
Configuration
Tweaking Algorithm Settings
Performance Considerations
Additional Resources
Preliminary Concepts
Each document passed to the clustering component is composed of several logical parts:
a unique identifier,
origin URL,
the title,
the main content,
a language code of the title and content.
The identifier part is mandatory, everything else is optional but at least one of the text fields (title or content) will
be required to make the clustering process reasonable. It is important to remember that logical document parts
must be mapped to a particular schema and its fields. The content (text) for clustering can be sourced from either
a stored text field or context-filtered using a highlighter, all these options are explained below in the configuration
section.
A clustering algorithm is the actual logic (implementation) that discovers relationships among the documents in
the search result and forms human-readable cluster labels. Depending on the choice of the algorithm the clusters
may (and probably will) vary. Solr comes with several algorithms implemented in the open source Carrot2 project
, commercial alternatives also exist.
Quick Start Example
The " techproducts" example included with Solr is pre-configured with all the necessary components for result
clustering - but they are disabled by default.
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