Efficiently selecting a title (the center of the cluster) for a cluster of strings

I have an (imperfectly) clustered string data, where the items in one cluster might look like this:

[ 
  Yellow ripe banana very tasty,
  Yellow ripe banana with little dots,
  Green apple with little dots,
  Green ripe banana - from the market, 
  Yellow ripe banana,
  Nice yellow ripe banana,
  Cool yellow ripe banana - my favourite,
  Yellow ripe,
  Yellow ripe
],

where the optimal title would be 'Yellow ripe banana'.

Currently, I am using simple heuristics - choosing the most common, or the shortest name if tie, - with the help of SQL GROUP BY. My data contains a large amount of such clusters, they change frequently, and, every time a new fruit is added to or removed from the cluster, the title for the cluster has to be re-calculated.

I would like to improve two things:

(1) Efficiency - e.g., compare the new fruit name to the title of the cluster only, and avoid grouping / phrase clustering of all fruit titles each time.

(2) Precision - instead of looking for the most common complete name, I would like to extract the most common phrase. The current algorithm would choose 'Yellow ripe', which repeats 2 times a开发者_StackOverflownd is the most common complete phrase; however, as the phrase, 'Yellow ripe banana' is the most common in the given set.

I am thinking of using Solr + Carrot2 (got no experience with the second). At this point, I do not need to cluster the documents - they are already clustered based on other parameters - I only need to choose the central phrase as the center/title of the cluster.

Any input is very appreciated, thanks!

Solr provides an analysis component called a ShingleFilter that you can use to create tokens from groups of adjacent words. If you put that in your analysis chain (ie apply it it incoming documents when you index them), and then compute facets for the resulting field with a query restricted to the "fruit cluster", you will be able to get a list of all distinct shingles along with their occurrence frequencies - I think you can even retrieve them sorted by frequency - which you can use easily I think to derive the title you want. Then when you add a new fruit, its shingles will automatically be included in the facet computations the next time around.

Just a bit more concrete version of this proposal:

create two fields: fruit_shingle, and cluster_id.

Configure fruit_shingle with the ShingleFilter and any other processing you might want (like tokenizing at word boundaries with maybe StandardTokenizer, prior to the ShingleFilter).

Configure cluster_id as a unique id, using whatever data you use to identify the clusters.

For each new fruit, store its text in fruit_shingle and its id in cluster_id.

Then retrieve facets for a query: "cluster_id:", and you will get a list of words, word pairs, word triplets, etc (shingles). You can configure the ShingleFilter to have a max length, I believe. Sort the facets by some combination of length and/or frequency that you deem appropriate and use that as the "title" of the fruit cluster.