1. A method comprising: identifying noise data using a demand factor that is based on relationships of items and categories to query terms of search queries; retrieving, from a plurality of listings, item data that is filtered from the noise data based on the demand factor; constructing, using a processor of a machine, at least one base cluster having at least one document with common item data stored in a suffix ordering; compacting the at least one base cluster to create a compacted cluster representation having a reduced duplicate suffix ordering amongst clusters; and merging the compacted cluster representation to generate a merged cluster based upon a first overlap value applied to the at least one document with common item data.
12. The method of claim 1 , further comprising: receiving a search query, the search query relating to item data; and extracting the item data from the merged cluster as a search result, the search result extracted based upon a similarity between the search query and the item data.