what is the difference between suggester component and carrot2 cluster in solr?

Question

I need to know in common language what is the difference between them and what are they used for exactly and how? I'm having a Solr project that suggests results based on queries as a personalization approach. which one can be used?

Answer 1

They're very different features. Carrot2 is a clusterer - ie it finds clusters of similar documents that belong together. That means that it attempts to determine which documents describe the same thing, and group them together based on these characteristics.

The suggester is component is mainly used for autocomplete-like features, where you're giving the user suggestions on what to search for (ie trying to guess what the user wants to accomplish before he or she has typed all of their query).

Neither is intended for personalization. You might want to look at Learning to rank to apply certain models based on what you know about the input from the user. You'll have to find out which features you have that describe your users and apply those as external feature information

There's also a feature to examine semantic knowledge graphs (ie "this concept is positively related to this other concept"), but that's probably on the side of what you're looking for.