Faceted Search today is getting more and more attention since it provides a more interactive way to browse vast amounts of data, without the well-known risk over-specifying your query, resulting in a 'no results found' message, leaving you without any clue of what might have been found:
"A good solution to these problems involves exposing the facets in dynamic taxonomies, so that the search user can see exactly the options they have available at any time. They can switch easily between searching and browsing, using their own terminology for search while recognizing the organization and vocabulary of the data."
However, Faceted Search today is dominated by commercial vendors providing limited functionality or limited scalability. Most implementations either process say the first 1000 hits, and thus provide limited accuracy, or they perform repetitive queries, one for each meta-data field, thus placing a severe limit on scalability.
Our research aims to create a high performance drill-down implementation that scales up well regarding both the number of records in the index as for the number of meta-data fields. We support both field-drill-down as well as term-drill-down (Faceted Search). Our DEMO server is currently off-line.
We are currently looking for sponsors to help make it Open Source.