diff --git a/BotSharp.NLP.UnitTest/SVMClassifierTest.cs b/BotSharp.NLP.UnitTest/SVMClassifierTest.cs
index 732af1f5..19e5a32b 100644
--- a/BotSharp.NLP.UnitTest/SVMClassifierTest.cs
+++ b/BotSharp.NLP.UnitTest/SVMClassifierTest.cs
@@ -39,7 +39,7 @@ namespace BotSharp.NLP.UnitTest
             sentences.Add("The sun in the sky is bright.");
             sentences.Add("We can see the shining sun, the bright sun.");
             Args args = new Args();
-            args.ModelFile = "C:\\Users\\bpeng\\Desktop\\BoloReborn\\BotSharp.NLP\\BotSharp.NLP.UnitTest\\wordvec_enu.bin";
+            args.ModelFile = "C:\\Users\\bpeng\\Desktop\\BoloReborn\\BotSharp\\BotSharp.WebHost\\App_Data\\wordvec_enu.bin";
             VectorGenerator vg = new VectorGenerator(args);
             var list = vg.Sentence2Vec(sentences);
         }
diff --git a/BotSharp.NLP/Classify/SVMClassifier.cs b/BotSharp.NLP/Classify/SVMClassifier.cs
index 4b28ee9e..124a49ea 100644
--- a/BotSharp.NLP/Classify/SVMClassifier.cs
+++ b/BotSharp.NLP/Classify/SVMClassifier.cs
@@ -124,7 +124,8 @@ namespace BotSharp.NLP.Classify
 
         public List<Node[]> GetData(List<Sentence> sentences)
         {
-            var extractor = new CountFeatureExtractor();
+            // var extractor = new CountFeatureExtractor();
+            var extractor = new Word2VecFeatureExtractor();
             extractor.Sentences = sentences;
             if(features != null)
             {
diff --git a/BotSharp.NLP/Featuring/Word2VecFeatureExtractor.cs b/BotSharp.NLP/Featuring/Word2VecFeatureExtractor.cs
new file mode 100644
index 00000000..bf6e2101
--- /dev/null
+++ b/BotSharp.NLP/Featuring/Word2VecFeatureExtractor.cs
@@ -0,0 +1,56 @@
+using System;
+using System.Collections.Generic;
+using System.Text;
+using Bigtree.Algorithm.Matrix;
+using Txt2Vec;
+
+namespace BotSharp.NLP.Featuring
+{
+    public class Word2VecFeatureExtractor : IFeatureExtractor
+    {
+        public int Dimension { get; set; }
+        public List<Sentence> Sentences { get; set; }
+        public List<Tuple<string, int>> Dictionary { get; set; }
+        public List<string> Features { get; set; }
+        public Shape Shape { get; set; }
+        public VectorGenerator Vg { get; set; }
+        public int SentenceVectorSize { get; set; }
+
+        public Word2VecFeatureExtractor()
+        {
+            Args args = new Args();
+            args.ModelFile = "C:\\Users\\bpeng\\Desktop\\BoloReborn\\BotSharp\\BotSharp.WebHost\\App_Data\\wordvec_enu.bin";
+            this.Vg = new VectorGenerator(args);
+            this.SentenceVectorSize = this.Vg.Model.VectorSize * MaxSentenceTokenCounts();
+        }
+
+        public void Vectorize()
+        {
+            Sentences.ForEach(s => {
+                Vec sentenceVec = new Vec();
+                s.Words.ForEach(word => {
+                    Vec wordVec = Vg.Word2Vec(word.Text);
+                    sentenceVec.VecNodes.AddRange(wordVec.VecNodes);
+                });
+                while (sentenceVec.VecNodes.Count != SentenceVectorSize)
+                {
+                    sentenceVec.VecNodes.Add(0);
+                }
+                s.Vector = sentenceVec.VecNodes.ToArray();
+            });
+        }
+
+        private int MaxSentenceTokenCounts()
+        {
+            int maxCount = 0;
+            Sentences.ForEach(s=> {
+                if (s.Words.Count > maxCount)
+                {
+                    maxCount = s.Words.Count;
+                }
+            });
+
+            return maxCount;
+        }
+    }
+}
diff --git a/BotSharp.NLP/Txt2Vec/VectorGenerator.cs b/BotSharp.NLP/Txt2Vec/VectorGenerator.cs
index 7c848031..fbf23aef 100644
--- a/BotSharp.NLP/Txt2Vec/VectorGenerator.cs
+++ b/BotSharp.NLP/Txt2Vec/VectorGenerator.cs
@@ -11,11 +11,13 @@ namespace Txt2Vec
 {
     public class VectorGenerator
     {
-        Txt2Vec.Model model = new Txt2Vec.Model();
+        public Model Model { get; set; }
+        // Txt2Vec.Model model = new Txt2Vec.Model();
         Dictionary<string, Vec> dict = new Dictionary<string, Vec>();
 
         public VectorGenerator(Args args)
         {
+            this.Model = new Txt2Vec.Model();
             bool bTxtFormat = false;
             string strModelFileName = args.ModelFile;
 
@@ -30,7 +32,7 @@ namespace Txt2Vec
                 throw new IOException();
             }
 
-            model.LoadModel(strModelFileName, bTxtFormat);
+            this.Model.LoadModel(strModelFileName, bTxtFormat);
         }
 
         public List<Vec> Sentence2Vec(List<string> sentences, WeightingScheme weightingScheme = WeightingScheme.AVG)
@@ -40,18 +42,20 @@ namespace Txt2Vec
             List<List<double>> weights = null;// tfidfGenerator.TFIDFWeightVectorsForSentences(sentences.ToArray());
 
             List<List<Vec>> matixList = new List<List<Vec>>();
-            
+            List<Vec> sentenceVectorList = new List<Vec>();
             sentences.ForEach (sentence=>{
-                List<Vec> sentenceVectorList = new List<Vec>();
-                string[] words = sentence.Split(' ');
-                foreach (string word in words)
-                {
-                    Vec vec = Word2Vec(word.ToLower());
-                    sentenceVectorList.Add(vec);
-                }
-                matixList.Add(sentenceVectorList);
+                //List<Vec> sentenceVectorList = new List<Vec>();
+                //string[] words = sentence.Split(' ');
+                //foreach (string word in words)
+                //{
+                //    Vec vec = Word2Vec(word.ToLower());
+                //    sentenceVectorList.Add(vec);
+                //}
+                //matixList.Add(sentenceVectorList);
             });
 
+            return sentenceVectorList;
+            /*
             List<Vec> vectorList = new List<Vec>();
             // Traverse each sentence
             for (int i = 0; i < sentences.Count; i++)
@@ -98,6 +102,7 @@ namespace Txt2Vec
                 
             }
             return vectorList;
+            */
         }
 
         public Vec SingleSentence2Vec(string sentence, WeightingScheme weightingScheme = WeightingScheme.AVG)
@@ -156,7 +161,7 @@ namespace Txt2Vec
         {
             Vec vec= new Vec();
 
-            Txt2Vec.Decoder decoder = new Txt2Vec.Decoder(model);
+            Txt2Vec.Decoder decoder = new Txt2Vec.Decoder(Model);
             string[] termList = new string[1];
             termList[0] = word;
             vec.VecNodes = decoder.ToVector(termList).ToList();
@@ -167,7 +172,7 @@ namespace Txt2Vec
         public double Similarity(Vec vec1, Vec vec2)
         {
             double score = 0;
-            for (int i = 0; i < model.VectorSize; i++)
+            for (int i = 0; i < Model.VectorSize; i++)
             {
                 score += vec1.VecNodes[i] * vec2.VecNodes[i];
             }