java.lang.Object
org.elasticsearch.common.lucene.search.XMoreLikeThis
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:
- 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() calls to generate a similarity query
- 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:
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setMinTermFreq(...)
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setMinDocFreq(...)
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setMaxDocFreq(...)
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setMinWordLen(...)
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setMaxWordLen(...)
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setMaxQueryTerms(...)
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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
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Field Summary
Modifier and TypeFieldDescriptionstatic final boolean
Boost terms in query based on score.static final String[]
Default field names.static final int
Ignore words which occur in more than this many docs.static final int
Default maximum number of tokens to parse in each example doc field that is not stored with TermVector support.static final int
Return a Query with no more than this many terms.static final int
Ignore words greater than this length or if 0 then this has no effect.static final int
Ignore words which do not occur in at least this many docs.static final int
Ignore terms with less than this frequency in the source doc.static final int
Ignore words less than this length or if 0 then this has no effect.static final Set<?>
Default set of stopwords. -
Constructor Summary
ConstructorDescriptionXMoreLikeThis
(org.apache.lucene.index.IndexReader ir, org.apache.lucene.search.similarities.TFIDFSimilarity sim) -
Method Summary
Modifier and TypeMethodDescriptionorg.apache.lucene.search.Query
Return a query that will return docs like the passed Readers.org.apache.lucene.search.Query
like
(org.apache.lucene.index.Fields... likeFields) Return a query that will return docs like the passed Fields.void
setAnalyzer
(org.apache.lucene.analysis.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 termsvoid
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
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
setSkipTerms
(Set<org.apache.lucene.index.Term> skipTerms) Sets a list of terms to never select fromvoid
setStopWords
(Set<?> stopWords) Set the set of stopwords.
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Field Details
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DEFAULT_MAX_NUM_TOKENS_PARSED
public static final int DEFAULT_MAX_NUM_TOKENS_PARSEDDefault maximum number of tokens to parse in each example doc field that is not stored with TermVector support.- See Also:
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DEFAULT_MIN_TERM_FREQ
public static final int DEFAULT_MIN_TERM_FREQIgnore terms with less than this frequency in the source doc.- See Also:
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DEFAULT_MIN_DOC_FREQ
public static final int DEFAULT_MIN_DOC_FREQIgnore words which do not occur in at least this many docs.- See Also:
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DEFAULT_MAX_DOC_FREQ
public static final int DEFAULT_MAX_DOC_FREQIgnore words which occur in more than this many docs.- See Also:
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DEFAULT_BOOST
public static final boolean DEFAULT_BOOSTBoost terms in query based on score.- See Also:
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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_LENGTHIgnore words less than this length or if 0 then this has no effect.- See Also:
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DEFAULT_MAX_WORD_LENGTH
public static final int DEFAULT_MAX_WORD_LENGTHIgnore words greater than this length or if 0 then this has no effect.- See Also:
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DEFAULT_STOP_WORDS
Default set of stopwords. If null means to allow stop words.- See Also:
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DEFAULT_MAX_QUERY_TERMS
public static final int DEFAULT_MAX_QUERY_TERMSReturn a Query with no more than this many terms.- See Also:
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BooleanQuery.getMaxClauseCount()
setMaxQueryTerms(int)
- Constant Field Values
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Constructor Details
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XMoreLikeThis
public XMoreLikeThis(org.apache.lucene.index.IndexReader ir, org.apache.lucene.search.similarities.TFIDFSimilarity sim)
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Method Details
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setBoostFactor
public void setBoostFactor(float boostFactor) Sets the boost factor to use when boosting terms -
setSkipTerms
Sets a list of terms to never select from -
setAnalyzer
public void setAnalyzer(org.apache.lucene.analysis.Analyzer analyzer) Sets the analyzer to use. All 'like' methods require an analyzer.- Parameters:
analyzer
- the analyzer to use to tokenize text.
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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.
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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.
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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
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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.
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setFieldNames
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.
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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.
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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.
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setStopWords
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
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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.
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like
Return a query that will return docs like the passed Readers. This was added in order to treat multi-value fields.- Returns:
- a query that will return docs like the passed Readers.
- Throws:
IOException
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like
public org.apache.lucene.search.Query like(org.apache.lucene.index.Fields... likeFields) throws IOException Return a query that will return docs like the passed Fields.- Returns:
- a query that will return docs like the passed Fields.
- Throws:
IOException
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