mirror of https://github.com/apache/lucene.git
LUCENE-577: initial checkin of SweetSpotSimilarity
git-svn-id: https://svn.apache.org/repos/asf/lucene/java/trunk@409472 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Chris M. Hostetter
parent
d96e03e914
commit
d2b63d328b
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@ -23,6 +23,9 @@ New features
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1. LUCENE-496: Command line tool for modifying the field norms of an
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existing index; added to contrib/miscellaneous. (Chris Hostetter)
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2. LUCENE-577: SweetSpotSimilarity added to contrib/miscellaneous.
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(Chris Hostetter)
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Bug fixes
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1. LUCENE-330: Fix issue of FilteredQuery not working properly within
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@ -0,0 +1,237 @@
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/**
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* Copyright 2006 The Apache Software Foundation
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.lucene.misc;
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import org.apache.lucene.search.Similarity;
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import org.apache.lucene.search.DefaultSimilarity;
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import java.util.Map;
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import java.util.HashMap;
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/**
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* A similarity with a lengthNorm that provides for a "platuea" of
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* equally good lengths, and tf helper functions.
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*
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* <p>
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* For lengthNorm, A global min/max can be specified to define the
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* platuea of lengths that should all have a norm of 1.0.
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* Below the min, and above the max the lengthNorm drops off in a
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* sqrt function.
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* </p>
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* <p>
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* A per field min/max can be specified if different fields have
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* different sweet spots.
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* </p>
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*
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* <p>
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* For tf, baselineTf and hyperbolicTf functions are provided, which
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* subclasses can choose between.
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* </p>
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*
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*/
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public class SweetSpotSimilarity extends DefaultSimilarity {
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private int ln_min = 1;
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private int ln_max = 1;
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private float ln_steep = 0.5f;
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private Map ln_mins = new HashMap(7);
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private Map ln_maxs = new HashMap(7);
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private Map ln_steeps = new HashMap(7);
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private float tf_base = 0.0f;
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private float tf_min = 0.0f;
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private float tf_hyper_min = 0.0f;
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private float tf_hyper_max = 2.0f;
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private double tf_hyper_base = 1.3d;
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private float tf_hyper_xoffset = 10.0f;
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public SweetSpotSimilarity() {
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super();
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}
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/**
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* Sets the baseline and minimum function variables for baselineTf
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*
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* @see #baselineTf
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*/
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public void setBaselineTfFactors(float base, float min) {
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tf_min = min;
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tf_base = base;
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}
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/**
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* Sets the function variables for the hyperbolicTf functions
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*
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* @param min the minimum tf value to ever be returned (default: 0.0)
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* @param max the maximum tf value to ever be returned (default: 2.0)
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* @param base the base value to be used in the exponential for the hyperbolic function (default: e)
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* @param xoffset the midpoint of the hyperbolic function (default: 10.0)
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* @see #hyperbolicTf
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*/
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public void setHyperbolicTfFactors(float min, float max,
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double base, float xoffset) {
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tf_hyper_min = min;
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tf_hyper_max = max;
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tf_hyper_base = base;
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tf_hyper_xoffset = xoffset;
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}
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/**
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* Sets the default function variables used by lengthNorm when no field
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* specifc variables have been set.
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*
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* @see #lengthNorm
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*/
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public void setLengthNormFactors(int min, int max, float steepness) {
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this.ln_min = min;
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this.ln_max = max;
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this.ln_steep = steepness;
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}
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/**
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* Sets the function variables used by lengthNorm for a specific named field
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*
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* @see #lengthNorm
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*/
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public void setLengthNormFactors(String field, int min, int max,
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float steepness) {
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ln_mins.put(field, new Integer(min));
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ln_maxs.put(field, new Integer(max));
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ln_steeps.put(field, new Float(steepness));
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}
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/**
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* Implimented as:
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* <code>
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* 1/sqrt( steepness * (abs(x-min) + abs(x-max) - (max-min)) + 1 )
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* </code>
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*
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* <p>
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* This degrades to <code>1/sqrt(x)</code> when min and max are both 1 and
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* steepness is 0.5
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* </p>
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*
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* <p>
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* :TODO: potential optimiation is to just flat out return 1.0f if numTerms
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* is between min and max.
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* </p>
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*
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* @see #setLengthNormFactors
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*/
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public float lengthNorm(String fieldName, int numTerms) {
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int l = ln_min;
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int h = ln_max;
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float s = ln_steep;
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if (ln_mins.containsKey(fieldName)) {
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l = ((Number)ln_mins.get(fieldName)).intValue();
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}
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if (ln_maxs.containsKey(fieldName)) {
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h = ((Number)ln_maxs.get(fieldName)).intValue();
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}
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if (ln_steeps.containsKey(fieldName)) {
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s = ((Number)ln_steeps.get(fieldName)).floatValue();
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}
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return (float)
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(1.0f /
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Math.sqrt
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(
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(
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s *
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(float)(Math.abs(numTerms - l) + Math.abs(numTerms - h) - (h-l))
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)
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+ 1.0f
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)
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);
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}
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/**
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* Delegates to baselineTf
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*
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* @see #baselineTf
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*/
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public float tf(int freq) {
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return baselineTf(freq);
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}
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/**
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* Implimented as:
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* <code>
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* (x <= min) ? base : sqrt(x+(base**2)-min)
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* </code>
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* ...but with a special case check for 0.
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* <p>
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* This degrates to <code>sqrt(x)</code> when min and base are both 0
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* </p>
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*
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* @see #setBaselineTfFactors
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*/
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public float baselineTf(float freq) {
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if (0.0f == freq) return 0.0f;
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return (freq <= tf_min)
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? tf_base
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: (float)Math.sqrt(freq + (tf_base * tf_base) - tf_min);
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}
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/**
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* Uses a hyperbolic tangent function that allows for a hard max...
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*
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* <code>
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* tf(x)=min+(max-min)/2*(((base**(x-xoffset)-base**-(x-xoffset))/(base**(x-xoffset)+base**-(x-xoffset)))+1)
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* </code>
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*
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* <p>
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* This code is provided as a convincience for subclasses that want
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* to use a hyperbolic tf function.
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* </p>
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*
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* @see #setHyperbolicTfFactors
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*/
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public float hyperbolicTf(float freq) {
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if (0.0f == freq) return 0.0f;
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final float min = tf_hyper_min;
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final float max = tf_hyper_max;
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final double base = tf_hyper_base;
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final float xoffset = tf_hyper_xoffset;
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final double x = (double)(freq - xoffset);
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final float result = min +
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(float)(
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(max-min) / 2.0f
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*
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(
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( ( Math.pow(base,x) - Math.pow(base,-x) )
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/ ( Math.pow(base,x) + Math.pow(base,-x) )
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)
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+ 1.0d
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)
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);
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return Float.isNaN(result) ? max : result;
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}
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}
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@ -0,0 +1,207 @@
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/**
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* Copyright 2006 The Apache Software Foundation
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package org.apache.lucene.misc;
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import org.apache.lucene.index.Term;
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import org.apache.lucene.search.Similarity;
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import org.apache.lucene.search.DefaultSimilarity;
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import org.apache.lucene.search.Query;
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import org.apache.lucene.search.TermQuery;
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import org.apache.lucene.search.PhraseQuery;
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import org.apache.lucene.search.DisjunctionMaxQuery;
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import org.apache.lucene.search.BooleanQuery;
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import org.apache.lucene.search.BooleanClause;
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import org.apache.lucene.search.BooleanClause.Occur;
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import junit.framework.Test;
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import junit.framework.TestCase;
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import junit.framework.TestSuite;
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import java.io.File;
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import java.math.BigDecimal;
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import java.util.Random;
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import java.util.Date;
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import java.util.List;
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import java.util.Arrays;
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import java.util.Map;
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import java.util.HashMap;
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import java.util.Iterator;
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/**
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* Test of the SweetSpotSimilarity
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*/
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public class SweetSpotSimilarityTest extends TestCase {
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public void testSweetSpotLengthNorm() {
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SweetSpotSimilarity ss = new SweetSpotSimilarity();
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ss.setLengthNormFactors(1,1,0.5f);
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Similarity d = new DefaultSimilarity();
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Similarity s = ss;
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// base case, should degrade
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for (int i = 1; i < 1000; i++) {
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assertEquals("base case: i="+i,
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d.lengthNorm("foo",i), s.lengthNorm("foo",i),
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0.0f);
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}
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// make a sweet spot
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ss.setLengthNormFactors(3,10,0.5f);
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for (int i = 3; i <=10; i++) {
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assertEquals("3,10: spot i="+i,
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1.0f, s.lengthNorm("foo",i),
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0.0f);
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}
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for (int i = 10; i < 1000; i++) {
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assertEquals("3,10: 10<x : i="+i,
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d.lengthNorm("foo",i-9), s.lengthNorm("foo",i),
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0.0f);
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}
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// seperate sweet spot for certain fields
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ss.setLengthNormFactors("bar",8,13, 0.5f);
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ss.setLengthNormFactors("yak",6,9, 0.5f);
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for (int i = 3; i <=10; i++) {
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assertEquals("f: 3,10: spot i="+i,
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1.0f, s.lengthNorm("foo",i),
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0.0f);
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}
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for (int i = 10; i < 1000; i++) {
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assertEquals("f: 3,10: 10<x : i="+i,
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d.lengthNorm("foo",i-9), s.lengthNorm("foo",i),
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0.0f);
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}
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for (int i = 8; i <=13; i++) {
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assertEquals("f: 8,13: spot i="+i,
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1.0f, s.lengthNorm("bar",i),
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0.0f);
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}
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for (int i = 6; i <=9; i++) {
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assertEquals("f: 6,9: spot i="+i,
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1.0f, s.lengthNorm("yak",i),
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0.0f);
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}
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for (int i = 13; i < 1000; i++) {
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assertEquals("f: 8,13: 13<x : i="+i,
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d.lengthNorm("foo",i-12), s.lengthNorm("bar",i),
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0.0f);
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}
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for (int i = 9; i < 1000; i++) {
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assertEquals("f: 6,9: 9<x : i="+i,
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d.lengthNorm("foo",i-8), s.lengthNorm("yak",i),
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0.0f);
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}
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// steepness
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ss.setLengthNormFactors("a",5,8,0.5f);
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ss.setLengthNormFactors("b",5,8,0.1f);
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for (int i = 9; i < 1000; i++) {
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assertTrue("s: i="+i+" : a="+ss.lengthNorm("a",i)+
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" < b="+ss.lengthNorm("b",i),
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ss.lengthNorm("a",i) < s.lengthNorm("b",i));
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}
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}
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public void testSweetSpotTf() {
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SweetSpotSimilarity ss = new SweetSpotSimilarity();
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Similarity d = new DefaultSimilarity();
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Similarity s = ss;
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// tf equal
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ss.setBaselineTfFactors(0.0f, 0.0f);
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for (int i = 1; i < 1000; i++) {
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assertEquals("tf: i="+i,
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d.tf(i), s.tf(i), 0.0f);
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}
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// tf higher
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ss.setBaselineTfFactors(1.0f, 0.0f);
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for (int i = 1; i < 1000; i++) {
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assertTrue("tf: i="+i+" : d="+d.tf(i)+
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" < s="+s.tf(i),
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d.tf(i) < s.tf(i));
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}
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// tf flat
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ss.setBaselineTfFactors(1.0f, 6.0f);
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for (int i = 1; i <=6; i++) {
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assertEquals("tf flat1: i="+i, 1.0f, s.tf(i), 0.0f);
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}
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ss.setBaselineTfFactors(2.0f, 6.0f);
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for (int i = 1; i <=6; i++) {
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assertEquals("tf flat2: i="+i, 2.0f, s.tf(i), 0.0f);
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}
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for (int i = 6; i <=1000; i++) {
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assertTrue("tf: i="+i+" : s="+s.tf(i)+
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" < d="+d.tf(i),
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s.tf(i) < d.tf(i));
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}
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// stupidity
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assertEquals("tf zero", 0.0f, s.tf(0), 0.0f);
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}
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public void testHyperbolicSweetSpot() {
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SweetSpotSimilarity ss = new SweetSpotSimilarity() {
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public float tf(int freq) {
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return hyperbolicTf(freq);
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}
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};
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ss.setHyperbolicTfFactors(3.3f, 7.7f, Math.E, 5.0f);
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Similarity s = ss;
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for (int i = 1; i <=1000; i++) {
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assertTrue("MIN tf: i="+i+" : s="+s.tf(i),
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3.3f <= s.tf(i));
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assertTrue("MAX tf: i="+i+" : s="+s.tf(i),
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s.tf(i) <= 7.7f);
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}
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assertEquals("MID tf", 3.3f+(7.7f - 3.3f)/2.0f, s.tf(5), 0.00001f);
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// stupidity
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assertEquals("tf zero", 0.0f, s.tf(0), 0.0f);
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}
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}
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