org.apache.lucene.queries.mlt

## Class MoreLikeThis

- java.lang.Object
- - org.apache.lucene.queries.mlt.MoreLikeThis

-     public final class MoreLikeThis
      extends Object

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

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

       You can use some heuristics to prune the set of terms, to avoid calling docFreq() 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);
       Reader 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:
  1. do your normal, Lucene setup for searching,
  2. create a MoreLikeThis,
  3. get the text of the doc you want to find similarities to
  4. then call one of the like() calls to generate a similarity query
  5. call the searcher to find the similar docs

  ### More Advanced Usage

  You may want to use `setFieldNames(...)` 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:
  - `setMinTermFreq(...)`
  - `setMinDocFreq(...)`
  - `setMaxDocFreq(...)`
  - `setMaxDocFreqPct(...)`
  - `setMinWordLen(...)`
  - `setMaxWordLen(...)`
  - `setMaxQueryTerms(...)`
  - `setMaxNumTokensParsed(...)`
  - `setStopWord(...)`

       Changes: Mark Harwood 29/02/04
       Some bugfixing, some refactoring, some optimisation.
       - bugfix: retrieveTerms(int docNum) was not working for indexes without a termvector -added missing code
       - bugfix: No significant terms being created for fields with a termvector - because
       was only counting one occurrence per term/field pair in calculations(ie not including frequency info from TermVector)
       - refactor: moved common code into isNoiseWord()
       - optimise: when no termvector support available - used maxNumTermsParsed to limit amount of tokenization

- - ### Field Summary

    Fields
    Modifier and Type | Field and Description
    --- | ---
    `static boolean` | `DEFAULT_BOOST` Boost terms in query based on score.
    `static String[]` | `DEFAULT_FIELD_NAMES` Default field names.
    `static int` | `DEFAULT_MAX_DOC_FREQ` Ignore words which occur in more than this many docs.
    `static int` | `DEFAULT_MAX_NUM_TOKENS_PARSED` Default maximum number of tokens to parse in each example doc field that is not stored with TermVector support.
    `static int` | `DEFAULT_MAX_QUERY_TERMS` Return a Query with no more than this many terms.
    `static int` | `DEFAULT_MAX_WORD_LENGTH` Ignore words greater than this length or if 0 then this has no effect.
    `static int` | `DEFAULT_MIN_DOC_FREQ` Ignore words which do not occur in at least this many docs.
    `static int` | `DEFAULT_MIN_TERM_FREQ` Ignore terms with less than this frequency in the source doc.
    `static int` | `DEFAULT_MIN_WORD_LENGTH` Ignore words less than this length or if 0 then this has no effect.
    `static Set<?>` | `DEFAULT_STOP_WORDS` Default set of stopwords.

  - ### Constructor Summary

    Constructors
    Constructor and Description
    `MoreLikeThis(IndexReader ir)` Constructor requiring an IndexReader.
    `MoreLikeThis(IndexReader ir, TFIDFSimilarity sim)`

  - ### Method Summary

    Methods
    Modifier and Type | Method and Description
    --- | ---
    `String` | `describeParams()` Describe the parameters that control how the "more like this" query is formed.
    `Analyzer` | `getAnalyzer()` Returns an analyzer that will be used to parse source doc with.
    `float` | `getBoostFactor()` Returns the boost factor used when boosting terms
    `String[]` | `getFieldNames()` Returns the field names that will be used when generating the 'More Like This' query.
    `int` | `getMaxDocFreq()` Returns the maximum frequency in which words may still appear.
    `int` | `getMaxNumTokensParsed()`
    `int` | `getMaxQueryTerms()` Returns the maximum number of query terms that will be included in any generated query.
    `int` | `getMaxWordLen()` Returns the maximum word length above which words will be ignored.
    `int` | `getMinDocFreq()` Returns the frequency at which words will be ignored which do not occur in at least this many docs.
    `int` | `getMinTermFreq()` Returns the frequency below which terms will be ignored in the source doc.
    `int` | `getMinWordLen()` Returns the minimum word length below which words will be ignored.
    `TFIDFSimilarity` | `getSimilarity()`
    `Set<?>` | `getStopWords()` Get the current stop words being used.
    `boolean` | `isBoost()` Returns whether to boost terms in query based on "score" or not.
    `Query` | `like(int docNum)` Return a query that will return docs like the passed lucene document ID.
    `Query` | `like(Reader r, String fieldName)` Return a query that will return docs like the passed Reader.
    `String[]` | `retrieveInterestingTerms(int docNum)`
    `String[]` | `retrieveInterestingTerms(Reader r, String fieldName)` Convenience routine to make it easy to return the most interesting words in a document.
    `PriorityQueue<Object[]>` | `retrieveTerms(int docNum)` Find words for a more-like-this query former.
    `PriorityQueue<Object[]>` | `retrieveTerms(Reader r, String fieldName)` Find words for a more-like-this query former.
    `void` | `setAnalyzer(Analyzer analyzer)` Sets the analyzer to use.
    `void` | `setBoost(boolean boost)` Sets whether to boost terms in query based on "score" or not.
    `void` | `setBoostFactor(float boostFactor)` Sets the boost factor to use when boosting terms
    `void` | `setFieldNames(String[] fieldNames)` Sets the field names that will be used when generating the 'More Like This' query.
    `void` | `setMaxDocFreq(int maxFreq)` Set the maximum frequency in which words may still appear.
    `void` | `setMaxDocFreqPct(int maxPercentage)` Set the maximum percentage in which words may still appear.
    `void` | `setMaxNumTokensParsed(int i)`
    `void` | `setMaxQueryTerms(int maxQueryTerms)` Sets the maximum number of query terms that will be included in any generated query.
    `void` | `setMaxWordLen(int maxWordLen)` Sets the maximum word length above which words will be ignored.
    `void` | `setMinDocFreq(int minDocFreq)` Sets the frequency at which words will be ignored which do not occur in at least this many docs.
    `void` | `setMinTermFreq(int minTermFreq)` Sets the frequency below which terms will be ignored in the source doc.
    `void` | `setMinWordLen(int minWordLen)` Sets the minimum word length below which words will be ignored.
    `void` | `setSimilarity(TFIDFSimilarity similarity)`
    `void` | `setStopWords(Set<?> stopWords)` Set the set of stopwords.

    - ### Methods inherited from class java.lang.Object

      `clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

- - ### Field Detail

    - #### DEFAULT_MAX_NUM_TOKENS_PARSED

          public static final int DEFAULT_MAX_NUM_TOKENS_PARSED

      Default maximum number of tokens to parse in each example doc field that is not stored with TermVector support.
      See Also:
        `getMaxNumTokensParsed()`, Constant Field Values

    - #### DEFAULT_MIN_TERM_FREQ

          public static final int DEFAULT_MIN_TERM_FREQ

      Ignore terms with less than this frequency in the source doc.
      See Also:
        `getMinTermFreq()`, `setMinTermFreq(int)`, Constant Field Values

    - #### DEFAULT_MIN_DOC_FREQ

          public static final int DEFAULT_MIN_DOC_FREQ

      Ignore words which do not occur in at least this many docs.
      See Also:
        `getMinDocFreq()`, `setMinDocFreq(int)`, Constant Field Values

    - #### DEFAULT_MAX_DOC_FREQ

          public static final int DEFAULT_MAX_DOC_FREQ

      Ignore words which occur in more than this many docs.
      See Also:
        `getMaxDocFreq()`, `setMaxDocFreq(int)`, `setMaxDocFreqPct(int)`, Constant Field Values

    - #### DEFAULT_BOOST

          public static final boolean DEFAULT_BOOST

      Boost terms in query based on score.
      See Also:
        `isBoost()`, `setBoost(boolean)`, Constant Field Values

    - #### DEFAULT_FIELD_NAMES

          public static final String[] DEFAULT_FIELD_NAMES

      Default field names. Null is used to specify that the field names should be looked up at runtime from the provided reader.

    - #### DEFAULT_MIN_WORD_LENGTH

          public static final int DEFAULT_MIN_WORD_LENGTH

      Ignore words less than this length or if 0 then this has no effect.
      See Also:
        `getMinWordLen()`, `setMinWordLen(int)`, Constant Field Values

    - #### DEFAULT_MAX_WORD_LENGTH

          public static final int DEFAULT_MAX_WORD_LENGTH

      Ignore words greater than this length or if 0 then this has no effect.
      See Also:
        `getMaxWordLen()`, `setMaxWordLen(int)`, Constant Field Values

    - #### DEFAULT_STOP_WORDS

          public static final Set<?> DEFAULT_STOP_WORDS

      Default set of stopwords. If null means to allow stop words.
      See Also:
        `setStopWords(java.util.Set<?>)`, `getStopWords()`

    - #### DEFAULT_MAX_QUERY_TERMS

          public static final int DEFAULT_MAX_QUERY_TERMS

      Return a Query with no more than this many terms.
      See Also:
        `BooleanQuery.getMaxClauseCount()`, `getMaxQueryTerms()`, `setMaxQueryTerms(int)`, Constant Field Values

  - ### Constructor Detail

    - #### MoreLikeThis

          public MoreLikeThis(IndexReader ir)

      Constructor requiring an IndexReader.

    - #### MoreLikeThis

          public MoreLikeThis(IndexReader ir,
                      TFIDFSimilarity sim)

  - ### Method Detail

    - #### getBoostFactor

          public float getBoostFactor()

      Returns the boost factor used when boosting terms
      Returns:
        the boost factor used when boosting terms
      See Also:
        `setBoostFactor(float)`

    - #### setBoostFactor

          public void setBoostFactor(float boostFactor)

      Sets the boost factor to use when boosting terms
      See Also:
        `getBoostFactor()`

    - #### getSimilarity

          public TFIDFSimilarity getSimilarity()

    - #### setSimilarity

          public void setSimilarity(TFIDFSimilarity similarity)

    - #### getAnalyzer

          public Analyzer getAnalyzer()

      Returns an analyzer that will be used to parse source doc with. The default analyzer is not set.
      Returns:
        the analyzer that will be used to parse source doc with.

    - #### setAnalyzer

          public void setAnalyzer(Analyzer analyzer)

      Sets the analyzer to use. An analyzer is not required for generating a query with the `like(int)` method, all other 'like' methods require an analyzer.
      Parameters:
        `analyzer` - the analyzer to use to tokenize text.

    - #### getMinTermFreq

          public int getMinTermFreq()

      Returns the frequency below which terms will be ignored in the source doc. The default frequency is the `DEFAULT_MIN_TERM_FREQ`.
      Returns:
        the frequency below which terms will be ignored in the source doc.

    - #### setMinTermFreq

          public void setMinTermFreq(int minTermFreq)

      Sets the frequency below which terms will be ignored in the source doc.
      Parameters:
        `minTermFreq` - the frequency below which terms will be ignored in the source doc.

    - #### getMinDocFreq

          public int getMinDocFreq()

      Returns the frequency at which words will be ignored which do not occur in at least this many docs. The default frequency is `DEFAULT_MIN_DOC_FREQ`.
      Returns:
        the frequency at which words will be ignored which do not occur in at least this many docs.

    - #### setMinDocFreq

          public void setMinDocFreq(int minDocFreq)

      Sets the frequency at which words will be ignored which do not occur in at least this many docs.
      Parameters:
        `minDocFreq` - the frequency at which words will be ignored which do not occur in at least this many docs.

    - #### getMaxDocFreq

          public int getMaxDocFreq()

      Returns the maximum frequency in which words may still appear. Words that appear in more than this many docs will be ignored. The default frequency is `DEFAULT_MAX_DOC_FREQ`.
      Returns:
        get the maximum frequency at which words are still allowed, words which occur in more docs than this are ignored.

    - #### setMaxDocFreq

          public void setMaxDocFreq(int maxFreq)

      Set the maximum frequency in which words may still appear. Words that appear in more than this many docs will be ignored.
      Parameters:
        `maxFreq` - the maximum count of documents that a term may appear in to be still considered relevant

    - #### setMaxDocFreqPct

          public void setMaxDocFreqPct(int maxPercentage)

      Set the maximum percentage in which words may still appear. Words that appear in more than this many percent of all docs will be ignored.
      Parameters:
        `maxPercentage` - the maximum percentage of documents (0-100) that a term may appear in to be still considered relevant

    - #### isBoost

          public boolean isBoost()

      Returns whether to boost terms in query based on "score" or not. The default is `DEFAULT_BOOST`.
      Returns:
        whether to boost terms in query based on "score" or not.
      See Also:
        `setBoost(boolean)`

    - #### setBoost

          public void setBoost(boolean boost)

      Sets whether to boost terms in query based on "score" or not.
      Parameters:
        `boost` - true to boost terms in query based on "score", false otherwise.
      See Also:
        `isBoost()`

    - #### getFieldNames

          public String[] getFieldNames()

      Returns the field names that will be used when generating the 'More Like This' query. The default field names that will be used is `DEFAULT_FIELD_NAMES`.
      Returns:
        the field names that will be used when generating the 'More Like This' query.

    - #### setFieldNames

          public void setFieldNames(String[] fieldNames)

      Sets the field names that will be used when generating the 'More Like This' query. Set this to null for the field names to be determined at runtime from the IndexReader provided in the constructor.
      Parameters:
        `fieldNames` - the field names that will be used when generating the 'More Like This' query.

    - #### getMinWordLen

          public int getMinWordLen()

      Returns the minimum word length below which words will be ignored. Set this to 0 for no minimum word length. The default is `DEFAULT_MIN_WORD_LENGTH`.
      Returns:
        the minimum word length below which words will be ignored.

    - #### setMinWordLen

          public void setMinWordLen(int minWordLen)

      Sets the minimum word length below which words will be ignored.
      Parameters:
        `minWordLen` - the minimum word length below which words will be ignored.

    - #### getMaxWordLen

          public int getMaxWordLen()

      Returns the maximum word length above which words will be ignored. Set this to 0 for no maximum word length. The default is `DEFAULT_MAX_WORD_LENGTH`.
      Returns:
        the maximum word length above which words will be ignored.

    - #### setMaxWordLen

          public void setMaxWordLen(int maxWordLen)

      Sets the maximum word length above which words will be ignored.
      Parameters:
        `maxWordLen` - the maximum word length above which words will be ignored.

    - #### setStopWords

          public void setStopWords(Set<?> stopWords)

      Set the set of stopwords. Any word in this set is considered "uninteresting" and ignored. Even if your Analyzer allows stopwords, you might want to tell the MoreLikeThis code to ignore them, as for the purposes of document similarity it seems reasonable to assume that "a stop word is never interesting".
      Parameters:
        `stopWords` - set of stopwords, if null it means to allow stop words
      See Also:
        `getStopWords()`

    - #### getStopWords

          public Set<?> getStopWords()

      Get the current stop words being used.
      See Also:
        `setStopWords(java.util.Set<?>)`

    - #### getMaxQueryTerms

          public int getMaxQueryTerms()

      Returns the maximum number of query terms that will be included in any generated query. The default is `DEFAULT_MAX_QUERY_TERMS`.
      Returns:
        the maximum number of query terms that will be included in any generated query.

    - #### setMaxQueryTerms

          public void setMaxQueryTerms(int maxQueryTerms)

      Sets the maximum number of query terms that will be included in any generated query.
      Parameters:
        `maxQueryTerms` - the maximum number of query terms that will be included in any generated query.

    - #### getMaxNumTokensParsed

          public int getMaxNumTokensParsed()

      Returns:
        The maximum number of tokens to parse in each example doc field that is not stored with TermVector support
      See Also:
        `DEFAULT_MAX_NUM_TOKENS_PARSED`

    - #### setMaxNumTokensParsed

          public void setMaxNumTokensParsed(int i)

      Parameters:
        `i` - The maximum number of tokens to parse in each example doc field that is not stored with TermVector support

    - #### like

          public Query like(int docNum)
                     throws IOException

      Return a query that will return docs like the passed lucene document ID.
      Parameters:
        `docNum` - the documentID of the lucene doc to generate the 'More Like This" query for.
      Returns:
        a query that will return docs like the passed lucene document ID.
      Throws:
        `IOException`

    - #### like

          public Query like(Reader r,
                   String fieldName)
                     throws IOException

      Return a query that will return docs like the passed Reader.
      Returns:
        a query that will return docs like the passed Reader.
      Throws:
        `IOException`

    - #### describeParams

          public String describeParams()

      Describe the parameters that control how the "more like this" query is formed.

    - #### retrieveTerms

          public PriorityQueue<Object[]> retrieveTerms(int docNum)
                                                throws IOException

      Find words for a more-like-this query former.
      Parameters:
        `docNum` - the id of the lucene document from which to find terms
      Throws:
        `IOException`

    - #### retrieveTerms

          public PriorityQueue<Object[]> retrieveTerms(Reader r,
                                              String fieldName)
                                                throws IOException

      Find words for a more-like-this query former. The result is a priority queue of arrays with one entry for every word in the document. Each array has 6 elements. The elements are:
      1. The word (String)
      2. The top field that this word comes from (String)
      3. The score for this word (Float)
      4. The IDF value (Float)
      5. The frequency of this word in the index (Integer)
      6. The frequency of this word in the source document (Integer)
      This is a somewhat "advanced" routine, and in general only the 1st entry in the array is of interest. This method is exposed so that you can identify the "interesting words" in a document. For an easier method to call see `retrieveInterestingTerms()`.
      Parameters:
        `r` - the reader that has the content of the document
        `fieldName` - field passed to the analyzer to use when analyzing the content
      Returns:
        the most interesting words in the document ordered by score, with the highest scoring, or best entry, first
      Throws:
        `IOException`
      See Also:
        `retrieveInterestingTerms(int)`

    - #### retrieveInterestingTerms

          public String[] retrieveInterestingTerms(int docNum)
                                            throws IOException

      Throws:
        `IOException`
      See Also:
        `retrieveInterestingTerms(java.io.Reader, String)`

    - #### retrieveInterestingTerms

          public String[] retrieveInterestingTerms(Reader r,
                                          String fieldName)
                                            throws IOException

      Convenience routine to make it easy to return the most interesting words in a document. More advanced users will call `retrieveTerms()` directly.
      Parameters:
        `r` - the source document
        `fieldName` - field passed to analyzer to use when analyzing the content
      Returns:
        the most interesting words in the document
      Throws:
        `IOException`
      See Also:
        `retrieveTerms(java.io.Reader, String)`, `setMaxQueryTerms(int)`

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