bts classifier

pfaedle.cfg

@@ -7,6 +7,8 @@
 routing_transition_penalty_fac:     0.0083
 routing_station_move_penalty_fac:	0.002
 
+station_similarity_classification_method: jaccard
+
 # Regular expressions and station comparision is
 # always case insensitive!
 station_normalize_chain:

src/pfaedle/PfaedleMain.cpp

@@ -61,6 +61,10 @@ using pfaedle::router::RouterImpl;
 using pfaedle::router::ShapeBuilder;
 using pfaedle::router::Stats;
 using pfaedle::statsimiclassifier::JaccardClassifier;
+using pfaedle::statsimiclassifier::StatsimiClassifier;
+using pfaedle::statsimiclassifier::BTSClassifier;
+using pfaedle::statsimiclassifier::EDClassifier;
+using pfaedle::statsimiclassifier::PEDClassifier;
 
 enum class RetCode {
   SUCCESS = 0,
@@ -277,7 +281,21 @@ int main(int argc, char** argv) {
         graphDimensions[filePost].second += nd->getAdjListOut().size();
       }
 
-      JaccardClassifier statsimiClassifier;
+      StatsimiClassifier* statsimiClassifier;
+
+      if (motCfg.routingOpts.statsimiMethod == "bts") {
+        statsimiClassifier = new BTSClassifier();
+      } else if (motCfg.routingOpts.statsimiMethod == "jaccard") {
+        statsimiClassifier = new JaccardClassifier();
+      } else if (motCfg.routingOpts.statsimiMethod == "ed") {
+        statsimiClassifier = new EDClassifier();
+      } else if (motCfg.routingOpts.statsimiMethod == "ped") {
+        statsimiClassifier = new PEDClassifier();
+      } else {
+        LOG(ERROR) << "Unknown station similarity classifier "
+                   << motCfg.routingOpts.statsimiMethod;
+        exit(1);
+      }
 
       Router* router = 0;
 
@@ -303,7 +321,7 @@ int main(int argc, char** argv) {
       }
 
       ShapeBuilder shapeBuilder(&gtfs[0], usedMots, motCfg, &graph, &fStops,
-                                &restr, &statsimiClassifier, router, cfg);
+                                &restr, statsimiClassifier, router, cfg);
 
       pfaedle::netgraph::Graph ng;
 
@@ -326,6 +344,7 @@ int main(int argc, char** argv) {
       }
 
       if (router) delete router;
+      if (statsimiClassifier) delete statsimiClassifier;
 
       if (cfg.writeGraph) {
         LOG(INFO) << "Outputting graph.json...";

src/pfaedle/config/MotConfigReader.cpp

@@ -61,6 +61,13 @@ void MotConfigReader::parse(const std::vector<std::string>& paths,
       cfg.routingOpts.transPenMethod = "exp";
     }
 
+    if (p.hasKey(secStr, "station_similarity_classification_method")) {
+      cfg.routingOpts.statsimiMethod =
+          p.getStr(secStr, "station_similarity_classification_method");
+    } else {
+      cfg.routingOpts.statsimiMethod = "bts";
+    }
+
     if (p.hasKey(secStr, "routing_use_stations")) {
       cfg.routingOpts.useStations = p.getBool(secStr, "routing_use_stations");
     } else {

src/pfaedle/router/Misc.h

@@ -62,6 +62,7 @@ struct RoutingOpts {
   double transitionPen;
   std::string transPenMethod;
   std::string emPenMethod;
+  std::string statsimiMethod;
 };
 
 // _____________________________________________________________________________
@@ -82,6 +83,7 @@ inline bool operator==(const RoutingOpts& a, const RoutingOpts& b) {
          fabs(a.nonStationPen - b.nonStationPen) < 0.01 &&
          a.transPenMethod == b.transPenMethod &&
          a.emPenMethod == b.emPenMethod &&
+         a.statsimiMethod == b.statsimiMethod &&
          a.useStations == b.useStations && a.popReachEdge == b.popReachEdge &&
          a.noSelfHops == b.noSelfHops;
 }

src/pfaedle/router/ShapeBuilder.cpp

@@ -47,7 +47,6 @@ using pfaedle::router::ShapeBuilder;
 using pfaedle::router::Stats;
 using pfaedle::router::TripForests;
 using pfaedle::router::TripTrie;
-using pfaedle::statsimiclassifier::JaccardClassifier;
 using pfaedle::trgraph::EdgeGrid;
 using pfaedle::trgraph::NodeGrid;
 using util::geo::latLngToWebMerc;

src/pfaedle/statsimi-classifier/StatsimiClassifier.cpp

@@ -9,7 +9,10 @@
 #include "pfaedle/statsimi-classifier/StatsimiClassifier.h"
 #include "util/geo/Geo.h"
 
+using pfaedle::statsimiclassifier::BTSClassifier;
+using pfaedle::statsimiclassifier::EDClassifier;
 using pfaedle::statsimiclassifier::JaccardClassifier;
+using pfaedle::statsimiclassifier::PEDClassifier;
 
 // _____________________________________________________________________________
 bool JaccardClassifier::similar(const std::string& nameA, const POINT& posA,
@@ -23,8 +26,52 @@ bool JaccardClassifier::similar(const std::string& nameA, const POINT& posA,
 // _____________________________________________________________________________
 bool JaccardClassifier::similar(const std::string& nameA,
                                 const std::string& nameB) const {
-  // hard similarity
+  return util::jaccardSimi(nameA, nameB) > 0.45;  // 0.45 from statsimi paper
-  if (nameA == nameB) return true;
+}
-
+
-  return util::jaccardSimi(nameA, nameB) > 0.45;  // 0.45 from paper
+// _____________________________________________________________________________
+bool BTSClassifier::similar(const std::string& nameA, const POINT& posA,
+                            const std::string& nameB, const POINT& posB) const {
+  UNUSED(posA);
+  UNUSED(posB);
+  return similar(nameA, nameB);
+}
+
+// _____________________________________________________________________________
+bool BTSClassifier::similar(const std::string& nameA,
+                            const std::string& nameB) const {
+  return util::btsSimi(nameA, nameB) > 0.85;  // 0.85 from statsimi paper
+}
+
+// _____________________________________________________________________________
+bool EDClassifier::similar(const std::string& nameA, const POINT& posA,
+                           const std::string& nameB, const POINT& posB) const {
+  UNUSED(posA);
+  UNUSED(posB);
+  return similar(nameA, nameB);
+}
+
+// _____________________________________________________________________________
+bool EDClassifier::similar(const std::string& nameA,
+                           const std::string& nameB) const {
+  double edSimi = 1.0 - ((util::editDist(nameA, nameB) * 1.0) /
+                         fmax(nameA.size(), nameB.size()));
+  return edSimi > 0.85;  // 0.85 from statsimi paper
+}
+
+// _____________________________________________________________________________
+bool PEDClassifier::similar(const std::string& nameA, const POINT& posA,
+                            const std::string& nameB, const POINT& posB) const {
+  UNUSED(posA);
+  UNUSED(posB);
+  return similar(nameA, nameB);
+}
+
+// _____________________________________________________________________________
+bool PEDClassifier::similar(const std::string& nameA,
+                            const std::string& nameB) const {
+  double a = (util::prefixEditDist(nameA, nameB) * 1.0) / (nameA.size() * 1.0);
+  double b = (util::prefixEditDist(nameB, nameA) * 1.0) / (nameB.size() * 1.0);
+  double pedSimi = 1.0 - fmin(a, b);
+  return pedSimi > 0.875;  // 0.875 average of values from statsimi paper
 }

src/pfaedle/statsimi-classifier/StatsimiClassifier.h

@@ -14,6 +14,7 @@ namespace statsimiclassifier {
 
 class StatsimiClassifier {
  public:
+  virtual ~StatsimiClassifier() {}
   virtual bool similar(const std::string& nameA, const POINT& posA,
                        const std::string& nameB, const POINT& posB) const = 0;
 
@@ -29,6 +30,30 @@ class JaccardClassifier : public StatsimiClassifier {
                        const std::string& nameB) const;
 };
 
+class BTSClassifier : public StatsimiClassifier {
+ public:
+  virtual bool similar(const std::string& nameA, const POINT& posA,
+                       const std::string& nameB, const POINT& posB) const;
+  virtual bool similar(const std::string& nameA,
+                       const std::string& nameB) const;
+};
+
+class EDClassifier : public StatsimiClassifier {
+ public:
+  virtual bool similar(const std::string& nameA, const POINT& posA,
+                       const std::string& nameB, const POINT& posB) const;
+  virtual bool similar(const std::string& nameA,
+                       const std::string& nameB) const;
+};
+
+class PEDClassifier : public StatsimiClassifier {
+ public:
+  virtual bool similar(const std::string& nameA, const POINT& posA,
+                       const std::string& nameB, const POINT& posB) const;
+  virtual bool similar(const std::string& nameA,
+                       const std::string& nameB) const;
+};
+
 }  // namespace statsimiclassifier
 }  // namespace pfaedle
 

src/util/String.h

@@ -6,17 +6,19 @@
 #define UTIL_STRING_H_
 
 #include <algorithm>
+#include <bitset>
 #include <cassert>
+#include <cmath>
 #include <codecvt>
 #include <cstring>
 #include <exception>
 #include <iomanip>
 #include <iostream>
 #include <locale>
+#include <set>
 #include <sstream>
 #include <string>
 #include <vector>
-#include <set>
 
 namespace util {
 
@@ -273,6 +275,12 @@ inline std::string implode(Iter begin, const Iter& end, const char* del) {
   return ss.str();
 }
 
+// _____________________________________________________________________________
+template <class T>
+inline std::string implode(const std::vector<T>& vec, const char* del) {
+  return implode(vec.begin(), vec.end(), del);
+}
+
 // _____________________________________________________________________________
 inline std::string normalizeWhiteSpace(const std::string& input) {
   std::string ret;
@@ -324,8 +332,9 @@ inline std::vector<std::string> tokenize(const std::string& str) {
 }
 
 // _____________________________________________________________________________
-inline double jaccardSimi(const std::string& a,
+inline double jaccardSimi(const std::string& a, const std::string& b) {
-                                            const std::string& b) {
+  if (a == b) return 1;
+
   std::set<std::string> sa, sb;
 
   auto toksA = tokenize(a);
@@ -349,9 +358,83 @@ inline double jaccardSimi(const std::string& a,
 }
 
 // _____________________________________________________________________________
-template <class T>
+inline double btsSimiInner(const std::vector<std::string>& toks,
-inline std::string implode(const std::vector<T>& vec, const char* del) {
+                           const std::string& b, double best) {
-  return implode(vec.begin(), vec.end(), del);
+  std::set<std::string> toksSet;
+  toksSet.insert(toks.begin(), toks.end());
+  std::vector<std::string> toksUniqSorted;
+  toksUniqSorted.insert(toksUniqSorted.begin(), toksSet.begin(), toksSet.end());
+
+  assert(toksUniqSorted.size() <= 8);
+
+  for (uint8_t v = 1; v <= pow(2, toksUniqSorted.size()); v++) {
+    std::bitset<8> bs(v);
+    std::vector<std::string> cur(bs.count());
+
+    size_t i = 0;
+    for (size_t j = 0; j < toksUniqSorted.size(); j++) {
+      if (bs[j]) {
+        cur[i] = toksUniqSorted[j];
+        i++;
+      }
+    }
+
+    double tmp = util::implode(cur, " ").size();
+
+    // ed between the two string will always be at least their length
+    // difference - if this is already too big, skip it right now
+    double dt = 1 - (fabs(tmp - b.size()) * 1.0) / (fmax(tmp, b.size()) * 1.0);
+
+    if (dt <= best) continue;
+
+    // cur is guaranteed to be sorted now
+    do {
+      const auto& comb = util::implode(cur, " ");
+
+      double d =
+          1 - ((editDist(comb, b) * 1.0) / (fmax(comb.size(), b.size()) * 1.0));
+
+      if (fabs(d - 1) < 0.0001) return 1;
+
+      if (d > best) best = d;
+    } while (std::next_permutation(cur.begin(), cur.end()));
+  }
+
+  return best;
+}
+
+// _____________________________________________________________________________
+inline double btsSimi(std::string a, std::string b) {
+  // this follows the implementation for the station similarity paper in
+  // https://github.com/ad-freiburg/statsimi/
+  if (a == b) return 1;
+
+  std::set<std::string> sa, sb;
+
+  auto toksA = tokenize(a);
+  auto toksB = tokenize(b);
+
+  // fallback to jaccard if the token set is too large
+  if (toksA.size() > 6 || toksB.size() > 6) {
+    return jaccardSimi(a, b);
+  }
+
+  if (toksA.size() > toksB.size()) {
+    std::swap(a, b);
+    std::swap(toksA, toksB);
+  }
+
+  // this is already our best known value - simply the edit
+  // distance similarity between the strings
+  double best = 1 - (editDist(a, b) * 1.0) / std::fmax(a.size(), b.size());
+
+  if (fabs(best) < 0.0001) return 0;
+
+  best = btsSimiInner(toksA, b, best);
+
+  if (fabs(best - 1) < 0.0001) return 1;
+
+  return btsSimiInner(toksB, a, best);
 }
 }  // namespace util
 

src/util/tests/TestMain.cpp

@@ -55,6 +55,28 @@ int main(int argc, char** argv) {
                                   {0, 5}}, 0.1) == approx(5));
   }
 
+  // ___________________________________________________________________________
+  {
+    TEST(util::btsSimi("", ""), ==, approx(1));
+    TEST(util::btsSimi("Hallo", "Test"), ==, approx(0));
+    TEST(util::btsSimi("Test", "Hallo"), ==, approx(0));
+    TEST(util::btsSimi("Test", "Test"), ==, approx(1));
+    TEST(util::btsSimi("Milner Road / Wandlee Road", "Wandlee Road"), ==, approx(1));
+    TEST(util::btsSimi("bla blubb blob", "blubb blib"), ==, approx(0.9));
+    TEST(util::btsSimi("St Pancras International", "London St Pancras"), ==, approx(0.588235));
+    TEST(util::btsSimi("Reiterstraße", "Reiterstraße Freiburg im Breisgau"), ==, approx(1));
+    TEST(util::btsSimi("Reiterstraße", "Reiter Freiburg im Breisgau"), ==, approx(.466666666));
+    TEST(util::btsSimi("AA", "Reiterstraße, Freiburg im Breisgau"), ==, approx(0));
+    TEST(util::btsSimi("blibb blabbel bla blubb blob", "blubb blib blabb"), ==, approx(0.875));
+    TEST(util::btsSimi("blibb blabbel bla blubb blobo", "blubb blib blabb blabo"), ==, approx(0.84));
+    TEST(util::btsSimi("blubb blib blabb", "blibb blabbel bla blubb blob"), ==, approx(0.875));
+    TEST(util::btsSimi("blubbb blib blabb blobo", "blibb blabbel bla blubb blobo"), ==, approx(0.84));
+    TEST(util::btsSimi("Reiter Freiburg im Breisgau", "Reiter Frei burg im Brei sgau"), ==, approx(0.931034));
+    // fallback to jaccard
+    TEST(util::btsSimi("Freiburg im Breisgau, Germany, Main Railway Station", "Main Railway Station Freiburg im Breisgau, Germany"), ==, approx(1));
+
+  }
+
   // ___________________________________________________________________________
   {
     std::string test = u8"Zürich, Hauptbahnhof (Nord)";