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/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
/**
* Highlighting search terms.
*
* 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:
*
*
* - Faster highlighting using Term vector support
*
- New formatting options to use color intensity to show informational value
*
- 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 constructors that 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.getMaxTermWeight
* method is useful when passed to the GradientFormatter constructor to define the top score which
* is associated with the top color.
*/
package org.apache.lucene.search.highlight;