1.add neighborhood model

2.the function in neighborhood model can handle different situation

config.py

@@ -8,7 +8,8 @@
           #['rmt','FM','RelatedMovieTag',['2']]
 
           #['basicSVD','SVD','Basic',[]]
-          ['ImplicitFeedbackSVD','SVD','ImplicitFeedback',[]]
+          #['ImplicitFeedbackSVD','SVD','ImplicitFeedback',[]]
+          ['NeighborhoodMovieTag', 'SVD' , 'Neighborhood' , ['MovieTag']]
           ] 
 
 # Defining models:

utils/SVDModel.py

@@ -1,19 +1,20 @@
 from Model import Model
 import ImplicitFeedbackFunctions as IFF #IFF for implicitFeedbackFunctions
+import neighborhoodFunctions as NF 
 class SVDModel(Model):
 
 ### Construct ###    
 
     def __init__(self,configModel,utils,config,strTrial):
-	    #This function is to set up different parameters only.
-        Model.__init__(self,configModel,utils,strTrial) #come from model!it's another class object.
+	    #This function is to set up different parameters.
+        Model.__init__(self,configModel,utils,strTrial) 
         self.configPath = utils.MODEL_CONFIG_PATH   + self.tag + \
                                               '_t' + strTrial
-        self.userHistoryReindexPath= utils.MODEL_TMP_PATH      + self.tag + \
-                                     '_userHistoryReindex' + '_t' + strTrial
-
+
         ### Baidu Specific ###
         ### Implicit Feedback Files ###
+        self.userHistoryReindexPath= utils.MODEL_TMP_PATH      + self.tag + \
+                                     '_userHistoryReindex' + '_t' + strTrial
         #The following 3 files are implicit feature files
         self.ImfeatTrain  = utils.MODEL_FEATURED_PATH + self.tag + \
                             '_Imtrain' + '_t' + strTrial
@@ -32,6 +33,16 @@ def __init__(self,configModel,utils,config,strTrial):
         ### End Implicit Feature Files ###
 
         self.regularizationFeedback = config.SVD_REGULARIZATION_FEEDBACK
+
+
+        ### Neighborhood Model Files###
+        if self.misc[0] == "MovieTag":
+            self.TagFilePath = self.movieTagPath
+            self.TagFileReindexPath = utils.MODEL_TMP_PATH      + self.tag + \
+                                           '_' + self.misc[0] + '_t' + strTrial
+            self.ShareTagPath = utils.MODEL_TMP_PATH      + self.tag + \
+                                           '_share_' + self.misc[0] + '_t' + strTrial
+        ### End Neighborhood Model Files###
         ### End Baidu Specific ###
 
         self.numIter              = config.SVD_NUM_ITER
@@ -180,7 +191,8 @@ def reIndex(self):
 
     def dataConvert(self):
         import os
-        if self.featureSet == 'Basic':
+        if self.featureSet == 'Basic' or \
+                self.featureSet == 'Neighborhood':
             os.system(self.SVDBufferPath + ' ' + 
                     self.featTrain + ' ' + self.runTrain)
             os.system(self.SVDBufferPath + ' ' + 
@@ -238,6 +250,8 @@ def setupFeatures(self):
         ### Baidu Specific Features ###
         if self.featureSet == 'ImplicitFeedback':
             self.setupImplicitFeatures()
+        if self.featureSet == 'Neighborhood':
+            self.NeighborhoodSetup()
         ### End Baidu Specific Features ###
 
     def basicConvert(self,fin,fout):
@@ -364,3 +378,23 @@ def setupImplicitFeatures(self):
         self.formatType = 1
         self.numUserFeedback = len(ItemDic)
 
+
+
+
+    def NeighborhoodSetup(self):
+        #second 
+        NSnoUser,NSnoMovie,NSAvg = NF.reIndex(self.bootTrain, self.TagFilePath, self.bootTest, self.bootCV, self.tmpTrain, self.TagFileReindexPath, self.tmpTest, self.tmpCV)
+
+        #third
+        NF.share(self.TagFileReindexPath,self.ShareTagPath)
+
+        #fourth
+        NumGlobal = NF.neighborhood(self.tmpTrain, self.ShareTagPath, self.tmpTest, self.featTrain, self.featTest)
+        NF.neighborhood(self.tmpCV, self.ShareTagPath, self.tmpTest, self.featCV, self.featTest)
+
+        # set the parameters.
+        self.numUser    =   NSnoUser
+        self.numMovie   =   NSnoMovie
+        self.numGlobal  =   NumGlobal + 1
+        self.avg        =   NSAvg
+