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    Namespace Lucene.Net.Search.Highlight

    The highlight package contains classes to provide "keyword in context" features typically used to highlight search terms in the text of results pages. The Highlighter class is the central component and can be used to extract the most interesting sections of a piece of text and highlight them, with the help of Fragmenter, fragment Scorer, and Formatter classes.

    Example Usage

      //... Above, create documents with two fields, one with term vectors (tv) and one without (notv)
      IndexSearcher searcher = new IndexSearcher(directory);
      QueryParser parser = new QueryParser("notv", analyzer);
      Query query = parser.parse("million");
    

    TopDocs hits = searcher.search(query, 10);

    SimpleHTMLFormatter htmlFormatter = new SimpleHTMLFormatter(); Highlighter highlighter = new Highlighter(htmlFormatter, new QueryScorer(query)); for (int i = 0; i < 10;="" i++)="" {="" int="" id="hits.scoreDocs[i].doc;" document="" doc="searcher.doc(id);" string="" text="doc.get(" notv");"="" tokenstream="" tokenstream="TokenSources.getAnyTokenStream(searcher.getIndexReader()," id,="" "notv",="" analyzer);="" textfragment[]="" frag="highlighter.getBestTextFragments(tokenStream," text,="" false,="" 10);//highlighter.getbestfragments(tokenstream,="" text,="" 3,="" "...");="" for="" (int="" j="0;" j="">< frag.length;="" j++)="" {="" if="" ((frag[j]="" !="null)" &&="" (frag[j].getscore()=""> 0)) { System.out.println((frag[j].toString())); } } //Term vector text = doc.get("tv"); tokenStream = TokenSources.getAnyTokenStream(searcher.getIndexReader(), hits.scoreDocs[i].doc, "tv", analyzer); frag = highlighter.getBestTextFragments(tokenStream, text, false, 10); for (int j = 0; j < frag.length;="" j++)="" {="" if="" ((frag[j]="" !="null)" &&="" (frag[j].getscore()=""> 0)) { System.out.println((frag[j].toString())); } } System.out.println("-------------"); }

    New features 06/02/2005

    This release adds options for encoding (thanks to Nicko Cadell). An "Encoder" implementation such as the new SimpleHTMLEncoder class can be passed to the highlighter to encode all those non-xhtml standard characters such as & into legal values. This simple class may not suffice for some languages - Commons Lang has an implementation that could be used: escapeHtml(String) in http://svn.apache.org/viewcvs.cgi/jakarta/commons/proper/lang/trunk/src/java/org/apache/commons/lang/StringEscapeUtils.java?rev=137958&view=markup

    New features 22/12/2004

    This release adds some new capabilities:

    1. Faster highlighting using Term vector support

    2. New formatting options to use color intensity to show informational value

    3. Options for better summarization by using term IDF scores to influence fragment selection

      The highlighter takes a TokenStream as input. Until now these streams have typically been produced using an Analyzer but the new class TokenSources provides helper methods for obtaining TokenStreams from the new TermVector position support (see latest CVS version).

    The new class GradientFormatter can use a scale of colors to highlight terms according to their score. A subtle use of color can help emphasise the reasons for matching (useful when doing "MoreLikeThis" queries and you want to see what the basis of the similarities are).

    The QueryScorer class has a new constructor which can use an IndexReader to derive the IDF (inverse document frequency) for each term in order to influence the score. This is useful for helping to extracting the most significant sections of a document and in supplying scores used by the new GradientFormatter to color significant words more strongly. The QueryScorer.getMaxWeight method is useful when passed to the GradientFormatter constructor to define the top score which is associated with the top color.

    Classes

    DefaultEncoder

    Simple IEncoder implementation that does not modify the output

    GradientFormatter

    Formats text with different color intensity depending on the score of the term.

    Highlighter

    Class used to markup highlighted terms found in the best sections of a text, using configurable IFragmenter, Scorer, IFormatter, IEncoder and tokenizers.

    InvalidTokenOffsetsException

    Exception thrown if TokenStream Tokens are incompatible with provided text

    NullFragmenter

    IFragmenter implementation which does not fragment the text. This is useful for highlighting the entire content of a document or field.

    OffsetLimitTokenFilter

    This Lucene.Net.Analysis.TokenFilter limits the number of tokens while indexing by adding up the current offset.

    PositionSpan

    Utility class to record Positions Spans

    This is a Lucene.NET INTERNAL API, use at your own risk

    QueryScorer

    IScorer implementation which scores text fragments by the number of unique query terms found. This class converts appropriate Lucene.Net.Search.Querys to Lucene.Net.Search.Spans.SpanQuerys and attempts to score only those terms that participated in generating the 'hit' on the document.

    QueryTermExtractor

    Utility class used to extract the terms used in a query, plus any weights. This class will not find terms for MultiTermQuery, RangeQuery and PrefixQuery classes so the caller must pass a rewritten query (see Rewrite(IndexReader)) to obtain a list of expanded terms.

    QueryTermScorer

    IScorer implementation which scores text fragments by the number of unique query terms found. This class uses the QueryTermExtractor class to process determine the query terms and their boosts to be used.

    SimpleFragmenter

    IFragmenter implementation which breaks text up into same-size fragments with no concerns over spotting sentence boundaries.

    SimpleHTMLEncoder

    Simple IEncoder implementation to escape text for HTML output

    SimpleHTMLFormatter

    Simple IFormatter implementation to highlight terms with a pre and post tag

    SimpleSpanFragmenter

    IFragmenter implementation which breaks text up into same-size fragments but does not split up Spans. This is a simple sample class.

    SpanGradientFormatter

    Formats text with different color intensity depending on the score of the term using the span tag. GradientFormatter uses a bgcolor argument to the font tag which doesn't work in Mozilla, thus this class.

    TextFragment

    Low-level class used to record information about a section of a document with a score.

    TokenGroup

    One, or several overlapping tokens, along with the score(s) and the scope of the original text

    TokenSources

    Hides implementation issues associated with obtaining a Lucene.Net.Analysis.TokenStream for use with the Highlighter - can obtain from term vectors with offsets and positions or from an Analyzer re-parsing the stored content. see TokenStreamFromTermVector

    TokenStreamFromTermPositionVector

    Lucene.Net.Analysis.TokenStream created from a term vector field.

    WeightedSpanTerm

    Lightweight class to hold term, weight, and positions used for scoring this term.

    WeightedSpanTermExtractor

    Class used to extract WeightedSpanTerms from a Lucene.Net.Search.Query based on whether Terms from the Lucene.Net.Search.Query are contained in a supplied Lucene.Net.Analysis.TokenStream.

    WeightedSpanTermExtractor.PositionCheckingMap<K>

    This class makes sure that if both position sensitive and insensitive versions of the same term are added, the position insensitive one wins.

    WeightedTerm

    Lightweight class to hold term and a Weight value used for scoring this term

    Interfaces

    IEncoder

    Encodes original text. The IEncoder works with the IFormatter to generate the output.

    IFormatter

    Processes terms found in the original text, typically by applying some form of mark-up to highlight terms in HTML search results pages.

    IFragmenter

    Implements the policy for breaking text into multiple fragments for consideration by the Highlighter class. A sophisticated implementation may do this on the basis of detecting end of sentences in the text.

    IScorer

    A IScorer is responsible for scoring a stream of tokens. These token scores can then be used to compute TextFragment scores.

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