Namespace Lucene.Net.Queries.Mlt

Document similarity query generators.

Classes

MoreLikeThis

Generate "more like this" similarity queries. Based on this mail:

Lucene does let you access the document frequency of terms, with Lucene.Net.Index.IndexReader.DocFreq(Lucene.Net.Index.Term).
Term frequencies can be computed by re-tokenizing the text, which, for a single document,
is usually fast enough.  But looking up the Lucene.Net.Index.IndexReader.DocFreq(Lucene.Net.Index.Term) of every term in the document is
probably too slow.


You can use some heuristics to prune the set of terms, to avoid calling Lucene.Net.Index.IndexReader.DocFreq(Lucene.Net.Index.Term) too much,
or at all.  Since you're trying to maximize a tf*idf score, you're probably most interested
in terms with a high tf. Choosing a tf threshold even as low as two or three will radically
reduce the number of terms under consideration.  Another heuristic is that terms with a
high idf (i.e., a low df) tend to be longer.  So you could threshold the terms by the
number of characters, not selecting anything less than, e.g., six or seven characters.
With these sorts of heuristics you can usually find small set of, e.g., ten or fewer terms
that do a pretty good job of characterizing a document.


It all depends on what you're trying to do.  If you're trying to eek out that last percent
of precision and recall regardless of computational difficulty so that you can win a TREC
competition, then the techniques I mention above are useless.  But if you're trying to
provide a "more like this" button on a search results page that does a decent job and has
good performance, such techniques might be useful.


An efficient, effective "more-like-this" query generator would be a great contribution, if
anyone's interested.  I'd imagine that it would take a Reader or a String (the document's
text), analyzer Analyzer, and return a set of representative terms using heuristics like those
above.  The frequency and length thresholds could be parameters, etc.


Doug

Initial Usage

This class has lots of options to try to make it efficient and flexible. The simplest possible usage is as follows. The bold fragment is specific to this class. 

IndexReader ir = ...
IndexSearcher is = ...

MoreLikeThis mlt = new MoreLikeThis(ir);
TextReader target = ... // orig source of doc you want to find similarities to
Query query = mlt.Like(target);

Hits hits = is.Search(query);
// now the usual iteration thru 'hits' - the only thing to watch for is to make sure
//you ignore the doc if it matches your 'target' document, as it should be similar to itself

Thus you:

  • do your normal, Lucene setup for searching,
  • create a MoreLikeThis,
  • get the text of the doc you want to find similarities to
  • then call one of the Like(TextReader, String) calls to generate a similarity query
  • call the searcher to find the similar docs

More Advanced Usage

You may want to use the setter for FieldNames so you can examine multiple fields (e.g. body and title) for similarity.

Depending on the size of your index and the size and makeup of your documents you may want to call the other set methods to control how the similarity queries are generated:

MoreLikeThisQuery

A simple wrapper for MoreLikeThis for use in scenarios where a Lucene.Net.Search.Query object is required eg in custom QueryParser extensions. At query.Rewrite() time the reader is used to construct the actual MoreLikeThis object and obtain the real Lucene.Net.Search.Query object.

ScoreTerm

An "interesting word" and related top field, score and frequency information.