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restaurant-search/util.go

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/*
* Copyright (c) 2015 Alex Yatskov <alex@foosoft.net>
* Author: Alex Yatskov <alex@foosoft.net>
*
* Permission is hereby granted, free of charge, to any person obtaining a copy of
* this software and associated documentation files (the "Software"), to deal in
* the Software without restriction, including without limitation the rights to
* use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
* the Software, and to permit persons to whom the Software is furnished to do so,
* subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
* FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
* COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
* IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
* CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
*/
package main
import (
"log"
"math"
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"strconv"
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"github.com/kellydunn/golang-geo"
)
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func fixFeatures(features featureMap) featureMap {
fixedFeatures := featureMap{
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"nearby": 0.0,
"accessible": 0.0,
"delicious": 0.0,
"accommodating": 0.0,
"affordable": 0.0,
"atmospheric": 0.0}
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for name, _ := range fixedFeatures {
value, _ := features[name]
fixedFeatures[name] = value
}
return fixedFeatures
}
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func innerProduct(features1 featureMap, features2 featureMap) float64 {
var result float64
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for key, value1 := range features1 {
value2, _ := features2[key]
result += value1 * value2
}
return result
}
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func walkMatches(entries records, features featureMap, minScore float64, callback func(record, float64)) {
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for _, entry := range entries {
if score := innerProduct(features, entry.features); score >= minScore {
callback(entry, score)
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}
}
}
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func statRecords(entries records, features featureMap, minScore float64) (float64, int) {
var compatibility float64
var count int
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walkMatches(entries, features, minScore, func(entry record, score float64) {
compatibility += entry.compatibility
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count++
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})
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return compatibility, count
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}
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func stepRange(min, max float64, steps int, callback func(float64)) {
stepSize := (max - min) / float64(steps)
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for i := 0; i < steps; i++ {
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stepMax := max - stepSize*float64(i)
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stepMin := stepMax - stepSize
stepMid := (stepMin + stepMax) / 2
callback(stepMid)
}
}
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func findRecords(entries records, features featureMap, minScore float64) records {
var foundEntries records
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walkMatches(entries, features, minScore, func(entry record, score float64) {
entry.score = score
foundEntries = append(foundEntries, entry)
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})
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return foundEntries
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}
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func calibrateMinScore(entries records, features featureMap, bracket namedBracket) float64 {
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bestScoreRank := -math.MaxFloat64
var bestMinScore float64
for minScore := float64(-len(features)); minScore <= float64(len(features)); minScore += 0.1 {
var scoreRank float64
for _, entry := range entries {
value, ok := entry.features[bracket.name]
if !ok {
continue
}
score := innerProduct(features, entry.features)
if score < minScore {
continue
}
if score > minScore {
if value >= bracket.min && value <= bracket.max {
dist := math.Abs(value - features[bracket.name])
scoreRank += 1 / (dist * dist)
} else {
dist := math.Min(math.Abs(value-bracket.min), math.Abs(value-bracket.max))
scoreRank -= 1 / (dist * dist)
}
}
}
if scoreRank > bestScoreRank {
bestScoreRank = scoreRank
bestMinScore = minScore
}
}
log.Printf("bestScoreRank: %f; bestMinScore: %f", bestScoreRank, bestMinScore)
return bestMinScore
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}
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func project(entries records, features featureMap, featureName string, minScore float64, steps int) []queryProjection {
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sampleFeatures := make(featureMap)
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for key, value := range features {
sampleFeatures[key] = value
}
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var projection []queryProjection
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stepRange(-1.0, 1.0, steps, func(sample float64) {
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sample, sampleFeatures[featureName] = sampleFeatures[featureName], sample
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compatibility, count := statRecords(entries, sampleFeatures, minScore)
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sample, sampleFeatures[featureName] = sampleFeatures[featureName], sample
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projection = append(projection, queryProjection{compatibility, count, sample})
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})
return projection
}
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func computeRecordGeo(entries records, context queryContext) {
distUserMin := math.MaxFloat64
distUserMax := 0.0
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for index := range entries {
entry := &entries[index]
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if context.geo != nil {
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userPoint := geo.NewPoint(context.geo.latitude, context.geo.longitude)
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entryPoint := geo.NewPoint(entry.geo.latitude, context.geo.longitude)
entry.distanceToUser = userPoint.GreatCircleDistance(entryPoint)
}
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distUserMin = math.Min(entry.distanceToUser, distUserMin)
distUserMax = math.Max(entry.distanceToUser, distUserMax)
}
distUserRange := distUserMax - distUserMin
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for index := range entries {
entry := &entries[index]
var accessible, nearby float64
if distUserRange > 0 {
nearby = -((entry.distanceToUser-distUserMin)/distUserRange - 0.5) * 2.0
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accessible = 1.0 - (entry.distanceToStn / context.walkingDist)
accessible = math.Max(accessible, -1.0)
accessible = math.Min(accessible, 1.0)
}
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entry.features["nearby"] = nearby
entry.features["accessible"] = accessible
}
}
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func computeRecordPopularity(entries records, context queryContext) {
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for index := range entries {
entry := &entries[index]
historyRows, err := db.Query("SELECT id FROM history WHERE reviewId = (?)", entry.id)
if err != nil {
log.Fatal(err)
}
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defer historyRows.Close()
var groupSum float64
var groupCount int
for historyRows.Next() {
var historyId int
if err := historyRows.Scan(&historyId); err != nil {
log.Fatal(err)
}
groupRows, err := db.Query("SELECT categoryId, categoryValue FROM historyGroups WHERE historyId = (?)", historyId)
if err != nil {
log.Fatal(err)
}
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defer groupRows.Close()
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recordProfile := make(featureMap)
for groupRows.Next() {
var categoryId int
var categoryValue float64
if err := groupRows.Scan(&categoryId, &categoryValue); err != nil {
log.Fatal(err)
}
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recordProfile[strconv.Itoa(categoryId)] = categoryValue
}
if err := groupRows.Err(); err != nil {
log.Fatal(err)
}
groupSum += innerProduct(recordProfile, context.profile)
groupCount++
}
if err := historyRows.Err(); err != nil {
log.Fatal(err)
}
if groupCount > 0 {
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entry.compatibility = groupSum / float64(groupCount)
}
}
}
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func getRecords(context queryContext) records {
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recordRows, err := db.Query("SELECT name, url, delicious, accommodating, affordable, atmospheric, latitude, longitude, distanceToStn, closestStn, accessCount, id FROM reviews")
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if err != nil {
log.Fatal(err)
}
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defer recordRows.Close()
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var entries []record
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for recordRows.Next() {
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var name, url, closestStn string
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var delicious, accommodating, affordable, atmospheric, latitude, longitude, distanceToStn float64
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var accessCount, id int
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recordRows.Scan(
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&name,
&url,
&delicious,
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&accommodating,
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&affordable,
&atmospheric,
&latitude,
&longitude,
&distanceToStn,
&closestStn,
&accessCount,
&id)
entry := record{
name: name,
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url: "http://www.tripadvisor.com" + url,
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distanceToStn: distanceToStn,
closestStn: closestStn,
accessCount: accessCount,
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geo: geoData{latitude, longitude},
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id: id}
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entry.features = featureMap{
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"delicious": delicious,
"accommodating": accommodating,
"affordable": affordable,
"atmospheric": atmospheric}
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entries = append(entries, entry)
}
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if err := recordRows.Err(); err != nil {
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log.Fatal(err)
}
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computeRecordPopularity(entries, context)
computeRecordGeo(entries, context)
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return entries
}