X-Git-Url: https://git.mdrn.pl/pylucene.git/blobdiff_plain/a2e61f0c04805cfcb8706176758d1283c7e3a55c..aaeed5504b982cf3545252ab528713250aa33eed:/lucene-java-3.4.0/lucene/contrib/highlighter/src/java/org/apache/lucene/search/highlight/package.html diff --git a/lucene-java-3.4.0/lucene/contrib/highlighter/src/java/org/apache/lucene/search/highlight/package.html b/lucene-java-3.4.0/lucene/contrib/highlighter/src/java/org/apache/lucene/search/highlight/package.html deleted file mode 100755 index b890f25..0000000 --- a/lucene-java-3.4.0/lucene/contrib/highlighter/src/java/org/apache/lucene/search/highlight/package.html +++ /dev/null @@ -1,99 +0,0 @@ - - - - - -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. -
  2. New formatting options to use color intensity to show informational value
    3. -
  3. Options for better summarization by using term IDF scores to influence fragment selection
    4. -
- -

-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.

- - - - - - \ No newline at end of file