/**
* Copyright 2005 The Apache Software Foundation
*
* Licensed 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.
*/
package org.apache.nutch.searcher;
import java.io.*;
import java.util.*;
import org.apache.lucene.analysis.Token;
import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.analysis.TokenStream;
import org.apache.nutch.util.NutchConf;
import org.apache.nutch.searcher.Summary.*;
import org.apache.nutch.analysis.NutchDocumentAnalyzer;
/** Implements hit summarization. */
public class Summarizer {
/** The number of context terms to display preceding and following matches.*/
private static final int SUM_CONTEXT =
NutchConf.get().getInt("searcher.summary.context", 5);
/** The total number of terms to display in a summary.*/
private static final int SUM_LENGTH =
NutchConf.get().getInt("searcher.summary.length", 20);
/** Converts text to tokens. */
private static final Analyzer ANALYZER = new NutchDocumentAnalyzer();
/**
* Class Excerpt represents a single passage found in the
* document, with some appropriate regions highlit.
*/
class Excerpt {
Vector passages = new Vector();
SortedSet tokenSet = new TreeSet();
int numTerms = 0;
/**
*/
public Excerpt() {
}
/**
*/
public void addToken(String token) {
tokenSet.add(token);
}
/**
* Return how many unique toks we have
*/
public int numUniqueTokens() {
return tokenSet.size();
}
/**
* How many fragments we have.
*/
public int numFragments() {
return passages.size();
}
public void setNumTerms(int numTerms) {
this.numTerms = numTerms;
}
public int getNumTerms() {
return numTerms;
}
/**
* Add a frag to the list.
*/
public void add(Fragment fragment) {
passages.add(fragment);
}
/**
* Return an Enum for all the fragments
*/
public Enumeration elements() {
return passages.elements();
}
}
/** Returns a summary for the given pre-tokenized text. */
public Summary getSummary(String text, Query query) throws IOException {
// Simplistic implementation. Finds the first fragments in the document
// containing any query terms.
//
// TODO: check that phrases in the query are matched in the fragment
Token[] tokens = getTokens(text); // parse text to token array
if (tokens.length == 0)
return new Summary();
String[] terms = query.getTerms();
HashSet highlight = new HashSet(); // put query terms in table
for (int i = 0; i < terms.length; i++)
highlight.add(terms[i]);
//
// Create a SortedSet that ranks excerpts according to
// how many query terms are present. An excerpt is
// a Vector full of Fragments and Highlights
//
SortedSet excerptSet = new TreeSet(new Comparator() {
public int compare(Object o1, Object o2) {
Excerpt excerpt1 = (Excerpt) o1;
Excerpt excerpt2 = (Excerpt) o2;
if (excerpt1 == null && excerpt2 != null) {
return -1;
} else if (excerpt1 != null && excerpt2 == null) {
return 1;
} else if (excerpt1 == null && excerpt2 == null) {
return 0;
}
int numToks1 = excerpt1.numUniqueTokens();
int numToks2 = excerpt2.numUniqueTokens();
if (numToks1 < numToks2) {
return -1;
} else if (numToks1 == numToks2) {
return excerpt1.numFragments() - excerpt2.numFragments();
} else {
return 1;
}
}
}
);
//
// Iterate through all terms in the document
//
int lastExcerptPos = 0;
for (int i = 0; i < tokens.length; i++) {
//
// If we find a term that's in the query...
//
if (highlight.contains(tokens[i].termText())) {
//
// Start searching at a point SUM_CONTEXT terms back,
// and move SUM_CONTEXT terms into the future.
//
int startToken = (i > SUM_CONTEXT) ? i-SUM_CONTEXT : 0;
int endToken = Math.min(i+SUM_CONTEXT, tokens.length);
int offset = tokens[startToken].startOffset();
int j = startToken;
//
// Iterate from the start point to the finish, adding
// terms all the way. The end of the passage is always
// SUM_CONTEXT beyond the last query-term.
//
Excerpt excerpt = new Excerpt();
if (i != 0) {
excerpt.add(new Summary.Ellipsis());
}
//
// Iterate through as long as we're before the end of
// the document and we haven't hit the max-number-of-items
// -in-a-summary.
//
while ((j < endToken) && (j - startToken < SUM_LENGTH)) {
//
// Now grab the hit-element, if present
//
Token t = tokens[j];
if (highlight.contains(t.termText())) {
excerpt.addToken(t.termText());
excerpt.add(new Fragment(text.substring(offset, t.startOffset())));
excerpt.add(new Highlight(text.substring(t.startOffset(),t.endOffset())));
offset = t.endOffset();
endToken = Math.min(j+SUM_CONTEXT, tokens.length);
}
j++;
}
lastExcerptPos = endToken;
//
// We found the series of search-term hits and added
// them (with intervening text) to the excerpt. Now
// we need to add the trailing edge of text.
//
// So if (j < tokens.length) then there is still trailing
// text to add. (We haven't hit the end of the source doc.)
// Add the words since the last hit-term insert.
//
if (j < tokens.length) {
excerpt.add(new Fragment(text.substring(offset,tokens[j].endOffset())));
}
//
// Remember how many terms are in this excerpt
//
excerpt.setNumTerms(j - startToken);
//
// Store the excerpt for later sorting
//
excerptSet.add(excerpt);
//
// Start SUM_CONTEXT places away. The next
// search for relevant excerpts begins at i-SUM_CONTEXT
//
i = j+SUM_CONTEXT;
}
}
//
// If the target text doesn't appear, then we just
// excerpt the first SUM_LENGTH words from the document.
//
if (excerptSet.size() == 0) {
Excerpt excerpt = new Excerpt();
int excerptLen = Math.min(SUM_LENGTH, tokens.length);
lastExcerptPos = excerptLen;
excerpt.add(new Fragment(text.substring(tokens[0].startOffset(), tokens[excerptLen-1].startOffset())));
excerpt.setNumTerms(excerptLen);
excerptSet.add(excerpt);
}
//
// Now choose the best items from the excerpt set.
// Stop when our Summary grows too large.
//
double tokenCount = 0;
Summary s = new Summary();
while (tokenCount <= SUM_LENGTH && excerptSet.size() > 0) {
Excerpt excerpt = (Excerpt) excerptSet.last();
excerptSet.remove(excerpt);
double tokenFraction = (1.0 * excerpt.getNumTerms()) / excerpt.numFragments();
for (Enumeration e = excerpt.elements(); e.hasMoreElements(); ) {
Fragment f = (Fragment) e.nextElement();
// Don't add fragments if it takes us over the max-limit
if (tokenCount + tokenFraction <= SUM_LENGTH) {
s.add(f);
}
tokenCount += tokenFraction;
}
}
if (tokenCount > 0 && lastExcerptPos < tokens.length)
s.add(new Ellipsis());
return s;
}
private Token[] getTokens(String text) throws IOException {
ArrayList result = new ArrayList();
TokenStream ts = ANALYZER.tokenStream("content", new StringReader(text));
for (Token token = ts.next(); token != null; token = ts.next()) {
result.add(token);
}
return (Token[])result.toArray(new Token[result.size()]);
}
/**
* Tests Summary-generation. User inputs the name of a
* text file and a query string
*/
public static void main(String argv[]) throws IOException {
// Test arglist
if (argv.length < 2) {
System.out.println("Usage: java org.apache.nutch.searcher.Summarizer <textfile> <queryStr>");
return;
}
Summarizer s = new Summarizer();
//
// Parse the args
//
File textFile = new File(argv[0]);
StringBuffer queryBuf = new StringBuffer();
for (int i = 1; i < argv.length; i++) {
queryBuf.append(argv[i]);
queryBuf.append(" ");
}
//
// Load the text file into a single string.
//
StringBuffer body = new StringBuffer();
BufferedReader in = new BufferedReader(new FileReader(textFile));
try {
System.out.println("About to read " + textFile + " from " + in);
String str = in.readLine();
while (str != null) {
body.append(str);
str = in.readLine();
}
} finally {
in.close();
}
// Convert the query string into a proper Query
Query query = Query.parse(queryBuf.toString());
System.out.println("Summary: '" + s.getSummary(body.toString(), query) + "'");
}
}