Add Hamming Distance KNN similarity metric for long property

algo/src/main/java/org/neo4j/gds/similarity/knn/metrics/HammingDistance.java

@@ -0,0 +1,52 @@
+/*
+ * Copyright (c) "Neo4j"
+ * Neo4j Sweden AB [http://neo4j.com]
+ *
+ * This file is part of Neo4j.
+ *
+ * Neo4j is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.neo4j.gds.similarity.knn.metrics;
+
+/**
+ * We compute the Hamming Distance,
+ * (https://en.wikipedia.org/wiki/Hamming_distance) and turn it into
+ * a similarity metric by clamping into 0..1 range using a linear
+ * transformation.
+ */
+public final class HammingDistance {
+    private HammingDistance() {}
+
+    public static double longMetric(long left, long right) {
+        return normalizeBitCount(
+                Long.bitCount(left ^ right)
+        );
+    }
+
+    /**
+     * We use unity-based normalization to scale the bit
+     * count to the [0-1] range:
+     * y = (x_i - min(x)) / (max(x) - min(x)) See
+     * https://stats.stackexchange.com/a/70807 for example.
+     * In our case, min(x) = 0 since you cannot have a negative
+     * bit count, and max(x) = 64 since in Java, a long is
+     * 64 bits in size.
+     *
+     * We then subtract the normalized range from 1.0 to map
+     * 1.0 as most similar, and 0.0 as least similar.
+     */
+    private static double normalizeBitCount(long bitCount) {
+        return 1.0 - (bitCount / 64.0);
+    }
+}

algo/src/main/java/org/neo4j/gds/similarity/knn/metrics/LongPropertySimilarityComputer.java

@@ -24,22 +24,20 @@
 
 final class LongPropertySimilarityComputer implements SimilarityComputer {
     private final NodePropertyValues nodePropertyValues;
+    private final LongPropertySimilarityMetric metric;
 
-    LongPropertySimilarityComputer(NodePropertyValues nodePropertyValues) {
+    LongPropertySimilarityComputer(NodePropertyValues nodePropertyValues, LongPropertySimilarityMetric metric) {
         if (nodePropertyValues.valueType() != ValueType.LONG) {
             throw new IllegalArgumentException("The property is not of type LONG");
         }
         this.nodePropertyValues = nodePropertyValues;
+        this.metric = metric;
     }
 
     @Override
     public double similarity(long firstNodeId, long secondNodeId) {
         var left = nodePropertyValues.longValue(firstNodeId);
         var right = nodePropertyValues.longValue(secondNodeId);
-        var abs = Math.abs(left - right);
-        if (abs == Long.MIN_VALUE) {
-            abs = Long.MAX_VALUE;
-        }
-        return 1.0 / (1.0 + abs);
+        return metric.compute(left, right);
     }
 }

algo/src/main/java/org/neo4j/gds/similarity/knn/metrics/LongPropertySimilarityMetric.java

@@ -0,0 +1,23 @@
+/*
+ * Copyright (c) "Neo4j"
+ * Neo4j Sweden AB [http://neo4j.com]
+ *
+ * This file is part of Neo4j.
+ *
+ * Neo4j is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.neo4j.gds.similarity.knn.metrics;
+interface LongPropertySimilarityMetric {
+    double compute(long left, long right);
+}

algo/src/main/java/org/neo4j/gds/similarity/knn/metrics/NormalizedAbsoluteDifference.java

@@ -0,0 +1,32 @@
+/*
+ * Copyright (c) "Neo4j"
+ * Neo4j Sweden AB [http://neo4j.com]
+ *
+ * This file is part of Neo4j.
+ *
+ * Neo4j is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.neo4j.gds.similarity.knn.metrics;
+
+public final class NormalizedAbsoluteDifference {
+    private NormalizedAbsoluteDifference() {}
+
+    public static double longMetric(long left, long right) {
+        var abs = Math.abs(left - right);
+        if (abs == Long.MIN_VALUE) {
+            abs = Long.MAX_VALUE;
+        }
+        return 1.0 / (1.0 + abs);
+    }
+}

algo/src/main/java/org/neo4j/gds/similarity/knn/metrics/SimilarityComputer.java

@@ -73,7 +73,11 @@ static SimilarityComputer ofProperty(
     ) {
         switch (properties.valueType()) {
             case LONG:
-                return ofLongProperty(properties);
+                return ofLongProperty(
+                    name,
+                    properties,
+                    defaultSimilarityMetric
+                );
             case DOUBLE:
                 return ofDoubleProperty(properties);
             case DOUBLE_ARRAY:
@@ -107,8 +111,15 @@ static SimilarityComputer ofDoubleProperty(NodePropertyValues nodePropertyValues
         return new DoublePropertySimilarityComputer(nodePropertyValues);
     }
 
-    static SimilarityComputer ofLongProperty(NodePropertyValues nodePropertyValues) {
-        return new LongPropertySimilarityComputer(nodePropertyValues);
+    static SimilarityComputer ofLongProperty(String name, NodePropertyValues properties, SimilarityMetric metric) {
+        switch (metric) {
+            case HAMMING_DISTANCE:
+                return new LongPropertySimilarityComputer(properties, HammingDistance::longMetric);
+            case NORMALIZED_ABSOLUTE_DIFFERENCE:
+                return new LongPropertySimilarityComputer(properties, NormalizedAbsoluteDifference::longMetric);
+            default:
+                throw unsupportedSimilarityMetric(name, properties.valueType(), metric);
+        }
     }
 
     static SimilarityComputer ofFloatArrayProperty(String name, NodePropertyValues properties, SimilarityMetric metric) {

algo/src/main/java/org/neo4j/gds/similarity/knn/metrics/SimilarityMetric.java

@@ -25,7 +25,9 @@
 import static org.neo4j.gds.utils.StringFormatting.toUpperCaseWithLocale;
 
 public enum SimilarityMetric {
-    JACCARD, OVERLAP, COSINE, EUCLIDEAN, PEARSON, LONG_PROPERTY_METRIC, DOUBLE_PROPERTY_METRIC, DEFAULT;
+    JACCARD, OVERLAP, COSINE, EUCLIDEAN, PEARSON,
+    NORMALIZED_ABSOLUTE_DIFFERENCE, DOUBLE_PROPERTY_METRIC,
+    HAMMING_DISTANCE, DEFAULT;
 
     public static SimilarityMetric parse(String value) {
         return SimilarityMetric.valueOf(toUpperCaseWithLocale(value));
@@ -34,7 +36,7 @@ public static SimilarityMetric parse(String value) {
     public static SimilarityMetric defaultMetricForType(ValueType valueType) {
         switch (valueType) {
             case LONG:
-                return LONG_PROPERTY_METRIC;
+                return NORMALIZED_ABSOLUTE_DIFFERENCE;
             case DOUBLE:
                 return DOUBLE_PROPERTY_METRIC;
             case DOUBLE_ARRAY:

algo/src/test/java/org/neo4j/gds/similarity/filteredknn/FilteredGenerateRandomNeighborsTest.java

@@ -68,7 +68,7 @@ public long size() {
             idMap,
             "myProperty",
             nodeProperties,
-            SimilarityMetric.LONG_PROPERTY_METRIC
+            SimilarityMetric.NORMALIZED_ABSOLUTE_DIFFERENCE
         );
 
         var random = new SplittableRandom();

algo/src/test/java/org/neo4j/gds/similarity/knn/GenerateRandomNeighborsTest.java

@@ -67,7 +67,7 @@ public long size() {
             idMap,
             "myProperty",
             nodeProperties,
-            SimilarityMetric.LONG_PROPERTY_METRIC
+            SimilarityMetric.NORMALIZED_ABSOLUTE_DIFFERENCE
         );
 
         var random = new SplittableRandom();

algo/src/test/java/org/neo4j/gds/similarity/knn/metrics/HammingDistanceTest.java

@@ -0,0 +1,40 @@
+/*
+ * Copyright (c) "Neo4j"
+ * Neo4j Sweden AB [http://neo4j.com]
+ *
+ * This file is part of Neo4j.
+ *
+ * Neo4j is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.neo4j.gds.similarity.knn.metrics;
+
+import org.junit.jupiter.api.Test;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+class HammingDistanceTest {
+    @Test
+    void shouldReturnFullCorrelationWhenArgsAreIdentical() {
+        double dist = HammingDistance.longMetric(12345L, 12345L);
+
+        assertEquals(1.0, dist);
+    }
+
+    @Test
+    void shouldReturnCorrectCorrelation() {
+        double dist = HammingDistance.longMetric(12345L, 54321L);
+
+        assertEquals(0.921875, dist);
+    }
+}

algo/src/test/java/org/neo4j/gds/similarity/knn/metrics/NormalizedAbsoluteDifferenceTest.java

@@ -0,0 +1,33 @@
+/*
+ * Copyright (c) "Neo4j"
+ * Neo4j Sweden AB [http://neo4j.com]
+ *
+ * This file is part of Neo4j.
+ *
+ * Neo4j is free software: you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License as published by
+ * the Free Software Foundation, either version 3 of the License, or
+ * (at your option) any later version.
+ *
+ * This program is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+ * GNU General Public License for more details.
+ *
+ * You should have received a copy of the GNU General Public License
+ * along with this program.  If not, see <http://www.gnu.org/licenses/>.
+ */
+package org.neo4j.gds.similarity.knn.metrics;
+
+import org.junit.jupiter.api.Test;
+
+import static org.junit.jupiter.api.Assertions.assertEquals;
+
+class NormalizedAbsoluteDifferenceTest {
+    @Test
+    void shouldComputeNormalizedAbsoluteDifference() {
+        double diff = NormalizedAbsoluteDifference.longMetric(1L, 2L);
+
+        assertEquals(0.5, diff);
+    }
+}

algo/src/test/java/org/neo4j/gds/similarity/knn/metrics/SimilarityComputerTest.java

@@ -66,16 +66,22 @@ void doublePropertySimilarityReturnsValuesBetween0And1(@ForAll @From("differentV
     }
 
     @Property
-    void longPropertySimilarityReturns1ForEqualValues(@ForAll @Positive long id) {
+    void longPropertySimilarityReturns1ForEqualValues(
+        @ForAll @Positive long id,
+        @ForAll @From("longMetrics") SimilarityMetric similarityMetric
+    ) {
         NodePropertyValues props = new LongTestPropertyValues(nodeId -> nodeId);
-        var sim = SimilarityComputer.ofLongProperty(props);
+        var sim = SimilarityComputer.ofLongProperty("", props, similarityMetric);
         assertThat(sim.similarity(id, id)).isEqualTo(1.0);
     }
 
     @Property
-    void longPropertySimilarityReturnsValuesBetween0And1(@ForAll @From("differentValues") LongLongPair ids) {
+    void longPropertySimilarityReturnsValuesBetween0And1(
+        @ForAll @From("differentValues") LongLongPair ids,
+        @ForAll @From("longMetrics") SimilarityMetric similarityMetric
+    ) {
         NodePropertyValues props = new LongTestPropertyValues(nodeId -> nodeId);
-        var sim = SimilarityComputer.ofLongProperty(props);
+        var sim = SimilarityComputer.ofLongProperty("", props, similarityMetric);
         assertThat(sim.similarity(ids.getOne(), ids.getTwo())).isStrictlyBetween(0.0, 1.0);
     }
 
@@ -305,6 +311,11 @@ final Arbitrary<LongLongPair> differentValues() {
             .map(n2 -> PrimitiveTuples.pair((long) n1, (long) n2)));
     }
 
+    @Provide("longMetrics")
+    final Arbitrary<SimilarityMetric> longMetrics() {
+        return Arbitraries.of(SimilarityMetric.NORMALIZED_ABSOLUTE_DIFFERENCE, SimilarityMetric.HAMMING_DISTANCE);
+    }
+
     @Provide("longArrayMetrics")
     final Arbitrary<SimilarityMetric> longArrayMetrics() {
         return Arbitraries.of(SimilarityMetric.JACCARD, SimilarityMetric.OVERLAP);