Bundle: MoreLikeThis

More Like This returns a list of similar documents that are related to a given document. This feature can be used, for example, when viewing an article. Many news sites show a list of the related articles at the bottom of the page. To accomplish this, the RavenDB More Like This uses the More Like This from the Lucene contrib project. To find out more about the algorithm, please read Aaron Johnson excellent blog post that is available here.


This bundle is built-in into a server and client and does not need any installation. All extensions are available under Raven.Client.Bundles.MoreLikeThis namespace.


In order to work, More Like This requires access to the text in the index, therefore, the index being queried needs to store the fields or store the term vectors for those fields.

public class Article
	public string Name { get; set; }
	public string ArticleBody { get; set; }

public class Articles_ByArticleBody : AbstractIndexCreationTask<Article>
	public Articles_ByArticleBody()
		Map = docs => from doc in docs
					  select new

		Stores.Add(x => x.ArticleBody, FieldStorage.Yes);
		Analyzers.Add(x => x.ArticleBody, typeof(StandardAnalyzer).FullName);

Basic Usage

More Like This has many defaults already set, and the simplest mode will satisfy the majority of the usage scenarios.

Article[] list = session.Advanced.MoreLikeThis<Article, Articles_ByArticleBody>(key);

More Like This will use all the fields defined in an index. To use only a specific field or fields, pass them in as the second parameter.

Article[] list = session.Advanced.MoreLikeThis<Article, Articles_ByArticleBody>(new MoreLikeThisQuery
	DocumentId = key,
	Fields = new[] { "ArticleBody" }

Advanced Usage

By passing in an object of the MoreLikeThisQuery type, the More Like This default can be changed.

  • Fields - Limit the fields that we search on to the specified field names only.
  • Boost - Boost terms in a query based on a score. Using this option may give more exact results by boosting the terms found by their score. The default is false.
  • BoostFactor - Factor that is used during term boosting. Default: 1.
  • IndexName - Name of an index to use in an operation.
  • DocumentId - The id of a document that will be used as the basis for comparison.
  • MapGroupFields - The values for the group fields mapping that will be used as the basis for comparison.
  • MaximumNumberOfTokensParsed - The maximum number of tokens to parse in each exemplary document field that is not stored with TermVector support. The default is 5000.
  • MaximumWordLength - Ignore words longer than the set limit; 0 has no effect. The default is 0.
  • MaximumQueryTerms - Return a Query with no more than this many terms. The default is 25.
  • MinimumDocumentFrequency - Ignore words which do not occur in at least this many documents. The default is 5.
  • MaximumDocumentFrequency - Ignore words which occur in more than this many documents. Default is Int32.MaxValue.
  • MaximumDocumentFrequencyPercentage - Ignore words which occur in more than this percentage of documents.
  • MinimumTermFrequency - Ignore terms with less than this frequency in the source doc. The default is 2.
  • MinimumWordLength - Ignore words less than this length; 0 has no effect. The default is 0.
  • StopWordsDocumentId - the document ID that contains the set of stop words (see below).
  • ResultsTransformer - name of a transformer that will be used.
  • TransformerParameters - parameters that will be passed to a transformer.

Stop Words

Some of Lucene analyzers have a built-in list of common English words that are usually not useful for searching (like "a", "as", "the" etc.). Those words are called stop words and they are considered to be uninteresting and ignored. If a used analyzer does not support stop words, or you need to overload them, you can specify your own set of stop words. A document with a list of stop words can be stored in the RavenDB by storing the StopWordsSetup document:

session.Store(new StopWordsSetup
	Id = "Config/Stopwords",
	StopWords = new List<string> { "I", "A", "Be" }

The document ID is then set in the MoreLikeThisQueryParameters.



Please note that default values for settings, like MinimumDocumentFrequency, MinimumTermFrequency, and MinimumWordLength, may result in filtering out related articles, especially when there is little data set (e.g. during development).