package com.bericotech.clavin.resolver;
import static org.apache.lucene.queryparser.classic.QueryParserBase.escape;
import java.io.File;
import java.io.IOException;
import java.util.ArrayList;
import java.util.HashSet;
import java.util.List;
import com.bericotech.clavin.extractor.LocationOccurrence;
import org.apache.lucene.analysis.Analyzer;
import org.apache.lucene.index.DirectoryReader;
import org.apache.lucene.queryparser.analyzing.AnalyzingQueryParser;
import org.apache.lucene.queryparser.classic.ParseException;
import org.apache.lucene.search.IndexSearcher;
import org.apache.lucene.search.Query;
import org.apache.lucene.search.Sort;
import org.apache.lucene.search.SortField;
import org.apache.lucene.search.TopDocs;
import org.apache.lucene.store.FSDirectory;
import org.apache.lucene.util.Version;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.bericotech.clavin.gazetteer.CountryCode;
import com.bericotech.clavin.index.BinarySimilarity;
import com.bericotech.clavin.index.WhitespaceLowerCaseAnalyzer;
import com.bericotech.clavin.util.ListUtils;
/*#####################################################################
*
* CLAVIN (Cartographic Location And Vicinity INdexer)
* ---------------------------------------------------
*
* Copyright (C) 2012-2013 Berico Technologies
* http://clavin.bericotechnologies.com
*
* ====================================================================
*
* 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.
*
* ====================================================================
*
* LuceneLocationResolver.java
*
*###################################################################*/
/**
* Resolves location names into GeoName objects.
*
* Takes location names extracted from unstructured text documents by
* {@link com.bericotech.clavin.extractor.LocationExtractor} and resolves them into the appropriate
* geographic entities (as intended by the document's author based on
* context) by finding the best match in a gazetteer.
*
*/
public class LuceneLocationResolver implements LocationResolver {
public final static Logger logger = LoggerFactory.getLogger(LuceneLocationResolver.class);
// Lucene index built from GeoNames gazetteer
private FSDirectory index;
private IndexSearcher indexSearcher;
private static Analyzer indexAnalyzer;
// maximum number of matches to be fetched from Lucene index
// (i.e., search depth) -- use a value of 1 to simply retrieve the
// matching geo entity having the highest population
private int maxHitDepth;
// maximum number of adjacent location name to consider during
// heuristic matching (i.e., search breadth) -- use a value of 1 to
// turn off context-based heuristics
private int maxContextWindow;
// custom Lucene sorting based on Lucene match score and the
// population of the GeoNames gazetteer entry represented by the
// matched index document
private static final Sort populationSort = new Sort(new SortField[]
{SortField.FIELD_SCORE, new SortField("population", SortField.Type.LONG, true)});
/**
* Builds a {@link LuceneLocationResolver} by loading a pre-built Lucene
* index from disk and setting configuration parameters for
* resolving location names to GeoName objects.
*
* @param indexDir Lucene index directory to be loaded
* @param maxHitDepth number of candidate matches to consider
* @param maxContextWindow how much context to consider when resolving
* @throws IOException
* @throws ParseException
*/
public LuceneLocationResolver(File indexDir, int maxHitDepth, int maxContextWindow) throws IOException, ParseException {
// load the Lucene index directory from disk
index = FSDirectory.open(indexDir);
// index employs simple lower-casing & tokenizing on whitespace
indexAnalyzer = new WhitespaceLowerCaseAnalyzer();
indexSearcher = new IndexSearcher(DirectoryReader.open(index));
// override default TF/IDF score to ignore multiple appearances
indexSearcher.setSimilarity(new BinarySimilarity());
this.maxHitDepth = maxHitDepth;
this.maxContextWindow = maxContextWindow;
// run an initial throw-away query just to "prime the pump" for
// the cache, so we can accurately measure performance speed
// per: http://wiki.apache.org/lucene-java/ImproveSearchingSpeed
indexSearcher.search(new AnalyzingQueryParser(Version.LUCENE_40,
"indexName", indexAnalyzer).parse("Reston"), null, maxHitDepth, populationSort);
}
/**
* Finds all matches (capped at {@link LuceneLocationResolver#maxHitDepth})
* in the Lucene index for a given location name.
*
* @param locationName name of the geographic location to be resolved
* @param fuzzy switch for turning on/off fuzzy matching
* @return list of ResolvedLocation objects as potential matches
* @throws IOException
* @throws ParseException
*/
private List<ResolvedLocation> getCandidateMatches(LocationOccurrence locationName, boolean fuzzy)
throws IOException, ParseException{
// santize the query input
String sanitizedLocationName = escape(locationName.text.toLowerCase());
try{
// Lucene query used to look for matches based on the
// "indexName" field
Query q = new AnalyzingQueryParser(Version.LUCENE_40,
"indexName", indexAnalyzer).parse("\"" + sanitizedLocationName + "\"");
// collect all the hits up to maxHits, and sort them based
// on Lucene match score and population for the associated
// GeoNames record
TopDocs results = indexSearcher.search(q, null, maxHitDepth, populationSort);
// initialize the return object
List<ResolvedLocation> candidateMatches = new ArrayList<ResolvedLocation>();
// see if anything was found
if (results.scoreDocs.length > 0) {
// one or more exact String matches found for this location name
for (int i = 0; i < results.scoreDocs.length; i++) {
// add each matching location to the list of candidates
ResolvedLocation location = new ResolvedLocation(indexSearcher.doc(results.scoreDocs[i].doc), locationName, false);
logger.debug("{}", location);
candidateMatches.add(location);
}
} else if (fuzzy) { // only if fuzzy matching is turned on
// no exact String matches found -- fallback to fuzzy search
// Using the tilde "~" makes this a fuzzy search. I compared this to FuzzyQuery
// with TopTermsBoostOnlyBooleanQueryRewrite, I like the output better this way.
// With the other method, we failed to match things like "Stra��enhaus Airport"
// as <Stra��enhaus>, and the match scores didn't make as much sense.
q = new AnalyzingQueryParser(Version.LUCENE_40, "indexName", indexAnalyzer).parse(sanitizedLocationName + "~");
// collect all the fuzzy matches up to maxHits, and sort
// them based on Lucene match score and population for the
// associated GeoNames record
results = indexSearcher.search(q, null, maxHitDepth, populationSort);
// see if anything was found with fuzzy matching
if (results.scoreDocs.length > 0) {
// one or more fuzzy matches found for this location name
for (int i = 0; i < results.scoreDocs.length; i++) {
// add each matching location to the list of candidates
ResolvedLocation location = new ResolvedLocation(indexSearcher.doc(results.scoreDocs[i].doc), locationName, true);
logger.debug(location + "{fuzzy}");
candidateMatches.add(location);
}
} else {
// drats, foiled again! no fuzzy matches found either!
// in this case, we'll return an empty list of
// candidate matches
logger.debug("No match found for: '{}'", locationName.text);
}
} else {
// no matches found and fuzzy matching is turned off
logger.debug("No match found for: '{}'", locationName.text);
}
return candidateMatches;
} catch (ParseException e) {
logger.error(String.format("Error resolving location for : '%s'", locationName.text), e);
throw e;
} catch (IOException e) {
logger.error(String.format("Error resolving location for : '%s'", locationName.text), e);
throw e;
}
}
/**
* Uses heuristics to select the best match for each location name
* extracted from a document, choosing from among a list of lists
* of candidate matches.
*
* Although not guaranteeing an optimal solution (enumerating &
* evaluating each possible combination is too costly), it does a
* decent job of cracking the "Springfield Problem" by selecting
* candidates that would make sense to appear together based on
* common country and admin1 codes (i.e., states or provinces).
*
* For example, if we also see "Boston" mentioned in a document
* that contains "Springfield," we'd use this as a clue that we
* ought to choose Springfield, MA over Springfield, IL or
* Springfield, MO.
*
* TODO: consider lat/lon distance in addition to shared
* CountryCodes and Admin1Codes.
*
* @param allCandidates list of lists of candidate matches for locations names
* @return list of best matches for each location name
*/
private List<ResolvedLocation> pickBestCandidates(List<List<ResolvedLocation>> allCandidates) {
// initialize return object
List<ResolvedLocation> bestCandidates = new ArrayList<ResolvedLocation>();
// variables used in heuristic matching
List<CountryCode> countries;
List<String> states;
float score;
// initial values for variables controlling recursion
float newMaxScore = 0;
float oldMaxScore = 0;
// controls window of Lucene hits for each location considered
// context-based heuristic matching, initialized as a "magic
// number" of *3* based on tests of the "Springfield Problem"
int candidateDepth = 3;
// keep searching deeper & deeper for better combinations of
// candidate matches, as long as the scores are improving
do {
// reset the threshold for recursion
oldMaxScore = newMaxScore;
// loop through all combinations up to the specified depth.
// first recursive call for each depth starts at index 0
for (List<ResolvedLocation> combo : generateAllCombos(allCandidates, 0, candidateDepth)) {
// these lists store the country codes & admin1 codes for each candidate
countries = new ArrayList<CountryCode>();
states = new ArrayList<String>();
for (ResolvedLocation location: combo) {
countries.add(location.geoname.primaryCountryCode);
states.add(location.geoname.admin1Code);
}
// unique-ify the lists to look for common country codes & admin1 codes
countries = new ArrayList<CountryCode>(new HashSet<CountryCode>(countries));
states = new ArrayList<String>(new HashSet<String>(states));
// calculate a score for this particular combination based on commonality
// of country codes & admin1 codes, and the cost of searching this deep
// TODO: tune this score calculation!
score = ((float)allCandidates.size() / (countries.size() + states.size())) / candidateDepth;
/* ***********************************************************
* "So, at last we meet for the first time for the last time."
*
* The fact that you're interested enough in CLAVIN to be
* reading this means we're interested in talking with you.
*
* Are you looking for a job, or are you in need of a
* customized solution built around CLAVIN?
*
* Drop us a line at clavin@bericotechnologies.com
*
* "What's the matter, Colonel Sandurz? CHICKEN?"
* **********************************************************/
// if this is the best we've seen during this loop, update the return value
if (score > newMaxScore) {
newMaxScore = score;
bestCandidates = combo;
}
}
// search one level deeper in the next loop
candidateDepth++;
} while (newMaxScore > oldMaxScore);
// keep searching while the scores are monotonically increasing
return bestCandidates;
}
/**
* Recursive helper function for
* {@link #pickBestCandidates}.
*
* Generates all combinations of candidate matches from each
* location, down to the specified depth through the lists.
*
* Adapted from:
* http://www.daniweb.com/software-development/java/threads/177956/generating-all-possible-combinations-from-list-of-sublists#post882553
*
* @param allCandidates list of lists of candidate matches for all location names
* @param index keeps track of which location we're working on for recursive calls
* @param depth max depth into list we're searching during this recursion
* @return all combinations of candidate matches for each location, down to the specified depth
*/
private List<List<ResolvedLocation>> generateAllCombos(List<List<ResolvedLocation>> allCandidates, int index, int depth) {
// stopping condition
if(index == allCandidates.size()) {
// return a list with an empty list
List<List<ResolvedLocation>> result = new ArrayList<List<ResolvedLocation>>();
result.add(new ArrayList<ResolvedLocation>());
return result;
}
// initialize return object
List<List<ResolvedLocation>> result = new ArrayList<List<ResolvedLocation>>();
// recursive call
List<List<ResolvedLocation>> recursive = generateAllCombos(allCandidates, index+1, depth);
// for each element of the first list of input, up to depth or list size
for(int j = 0; j < Math.min(allCandidates.get(index).size(), depth); j++) {
// add the element to all combinations obtained for the rest of the lists
for(int k = 0; k < recursive.size(); k++) {
List<ResolvedLocation> newList = new ArrayList<ResolvedLocation>();
// add element of the first list
newList.add(allCandidates.get(index).get(j));
// copy a combination from recursive
for(ResolvedLocation listItem : recursive.get(k))
newList.add(listItem);
// add new combination to result
result.add(newList);
}
}
return result;
}
/**
* Resolves the supplied list of location names into
* {@link ResolvedLocation}s containing {@link com.bericotech.clavin.gazetteer.GeoName} objects.
*
* Calls {@link LuceneLocationResolver#getCandidateMatches} on
* each location name to find all possible matches, then uses
* heuristics to select the best match for each by calling
* {@link LuceneLocationResolver#pickBestCandidates}.
*
* @param locations list of location names to be resolved
* @param fuzzy switch for turning on/off fuzzy matching
* @return list of {@link ResolvedLocation} objects
* @throws ParseException
* @throws IOException
**/
@Override
public List<ResolvedLocation> resolveLocations(List<LocationOccurrence> locations, boolean fuzzy) throws IOException, ParseException {
// are you forgetting something?
if (locations == null)
return new ArrayList<ResolvedLocation>();
if (maxHitDepth > 1) { // perform context-based heuristic matching
// stores all possible matches for each location name
List<List<ResolvedLocation>> allCandidates = new ArrayList<List<ResolvedLocation>>();
// loop through all the location names
for (LocationOccurrence location : locations) {
// get all possible matches
List<ResolvedLocation> candidates = getCandidateMatches(location, fuzzy);
// if we found some possible matches, save them
if (candidates.size() > 0)
allCandidates.add(candidates);
}
// initialize return object
List<ResolvedLocation> bestCandidates = new ArrayList<ResolvedLocation>();
// split-up allCandidates into reasonably-sized chunks to
// limit computational load when heuristically selecting
// the best matches
for (List<List<ResolvedLocation>> theseCandidates : ListUtils.chunkifyList(allCandidates, maxContextWindow)) {
// select the best match for each location name based
// based on heuristics
bestCandidates.addAll(pickBestCandidates(theseCandidates));
}
return bestCandidates;
} else { // use no heuristics, simply choose matching location with greatest population
// initialize return object
List<ResolvedLocation> resolvedLocations = new ArrayList<ResolvedLocation>();
// stores possible matches for each location name
List<ResolvedLocation> candidateLocations;
// loop through all the location names
for (LocationOccurrence location : locations) {
// choose the top-sorted candidate for each individual
// location name
candidateLocations = getCandidateMatches(location, fuzzy);
// if a match was found, add it to the return list
if (candidateLocations.size() > 0)
resolvedLocations.add(candidateLocations.get(0));
}
return resolvedLocations;
}
}
}