Affects Version/s: None
Fix Version/s: None
Component/s: contrib - Clustering
Currently, Carrot2 search results clustering component creates clusters based on the raw text of a field. The reason for this is that Carrot2 aims to create meaningful cluster labels by using sequences of words taken directly from the documents' text (including stop words: Development of Lucene and Solr is more readable than Development Lucene Solr). The easiest way of providing input for such a process was feeding Carrot2 with raw (stored) document content.
It is, however, possible to take into account of the field's filters during clustering. Because Carrot2 does not currently expose an API for feeding pre-tokenized input, the clustering component would need to:
1. get raw text of the field,
2. run it through the field's char filters, tokenizers and selected token filters (omitting e.g. stop words filter and stemmers, Carrot2 needs the original words to produce readable cluster labels),
3. glue the output back into a string and feed to Carrot2 for clustering.
In the future, to eliminate step 3, we could modify Carrot2 to accept pre-tokenized content.