Hi Antonio,
> To answer your question in terms of minimum term is, I am working with > "joke text" very short in length so the clusters are not so meaning full.. I > mean lot of adverbs and nouns, I thought increasing it might give me less > cluster but bit more meaningful (maybe not). Clustering this type of content (jokes, blogs) is tricky for Carrot2 algorithms, mostly because such input contains relatively little "informative" words (nouns, noun phrases) which are good for cluster labels, and more narrative ones (verbs, adjectives), which usually don't lead to meaningful labels / clusters. So I think the way to go would be to tune the clustering algorithm's stop words / stop label dictionaries to exclude the labels you don't like. I can't guarantee you can get decent clusters with this technique, but it's worth giving a try. Here's how to do that: 1. Download Carrot2 Clustering Workbench from: http://project.carrot2.org/download.html 2. Attach your Solr instance as a document source: http://download.carrot2.org/head/manual/#section.getting-started.solr 3. Try tuning the stop words / labels to get more meaningful labels: http://download.carrot2.org/head/manual/#section.advanced-topics.fine-tuning For more advice you may want to post your questions on Carrot2 forum: http://project.carrot2.org/forum.html. Hope that helps. Cheers, Staszek
