public List<Recommendation_Meta_Item> GetListR1R4_ForNewUsers(Predict_DAO_MC dao, Dictionary<string, double> UCA) { double M = 1; if (UCA.ContainsKey("MEANS_VALUE")) M = UCA["MEANS_VALUE"]; List<Recommendation_Meta_Item> list = new List<Recommendation_Meta_Item>(); //Content is cleared by M.C. Nguyen 19.9.2015 return list; }
public List<ADDGAP> GetListOfNewGAP(Predict_DAO_MC a) { List<ADDGAP> lst = new List<ADDGAP>(); try { lst = a.GetListOfNewGAP(); } catch (Exception) { throw; } return lst; }
public List<ClusterInfo> GetListCluster() { Predict_DAO_MC a = new Predict_DAO_MC(); List<ClusterInfo> list = new List<ClusterInfo>(); try { a.beginTransaction(); list = a.GetListCluster(); a.commitTransaction(); return list; } catch (Exception ex) { a.rollbackTransaction(); throw ex; } }
public void RemoveDuplicateR3R1() { Predict_DAO_MC a = new Predict_DAO_MC(); try { a.RemoveDuplicateR3R1(); } catch (Exception) { throw; } }
public void R3(Predict_DAO_MC dao, RecommdationSchedule schedule, int nbR3, Dictionary<string, double> UCA, List<QTY_GAP> lst) { List<Recommendation_Meta_Item> list = GetRecommendationR3(dao, nbR3); list = GetQuantityTraditionalUsersR3(dao, list, UCA); dao.RemoveDuplicateR3R1(); Normaliser(list); AddGAPtoListRecommends(lst, list); dao.InsertList(list, schedule); }
public void R4(Predict_DAO_MC dao, RecommdationSchedule schedule, double paramR4, Dictionary<string, double> UCA, List<QTY_GAP> lst) { List<Recommendation_Meta_Item> list = GetRecommendationR4(dao, paramR4, UCA); Normaliser(list); AddGAPtoListRecommends(lst, list); dao.InsertList(list, schedule); }
//Corrected by MC. NGUYEN 22.10.2014 public void R1(Predict_DAO_MC dao, RecommdationSchedule schedule, int nbR1, Dictionary<string, double> UCA, List<QTY_GAP> list) { //Get recommendations for traditional users List<Recommendation_Meta_Item> lrc_ForUserTra = getListRecommendation_R1_TraditionalUsers(dao, nbR1); lrc_ForUserTra = GetQuantityTraditionalUsers(dao, lrc_ForUserTra, UCA); Normaliser(lrc_ForUserTra); AddGAPtoListRecommends(list, lrc_ForUserTra); dao.InsertList(lrc_ForUserTra, schedule); }
public void R1R4_FOR_NEW_USERS(Predict_DAO_MC dao, RecommdationSchedule schedule, Dictionary<string, double> UCA) { List<Recommendation_Meta_Item> lrc_ForNewUsers = GetListR1R4_ForNewUsers(dao, UCA); // lrc_ForNewUsers = GetQuantityNewUsers(dao, lrc_ForNewUsers); Normaliser(lrc_ForNewUsers); dao.InsertListNewUser(lrc_ForNewUsers, schedule); }
public void LoadRecommendation(string LoginID) { Predict_DAO_MC dao = null; RecommdationSchedule schedule = new RecommdationSchedule(); schedule.Log = "Recommendation"; schedule.LoginID = LoginID; Predict_MC predictMC = new Predict_MC(); try { dao = new Predict_DAO_MC(); dao.beginTransaction(); RecommdationSchedule currentSchedule = dao.addRecommdationSchedule(schedule); // Settings st = getSettings(); Settings r = predictMC.GetRecommendationSeting(dao); Dictionary<string, double> UCA = predictMC.getUCA(dao); //Data service IntergrationManager manager = new IntergrationManager(); manager.execute(); //Learn the quantity GAP List<ADDGAP> lstADDGAP = predictMC.GetListOfNewGAP(dao); //get list of new GAP List<QTY_GAP> lstGAP = predictMC.UpdateQTYGap(dao, lstADDGAP); //Update new GAP and return the GAP Matrix //Clustering service new ClusterUsers().startClusteringAuto(); /* * * * this paragraph need to rewrite * * */ //C4 ComputeConfident(dao); // C5 ComputeDIST(dao); //===================================================================================== //dao.CLEAN_RECOMMENDATION(); //// C6 - MC DateTime startC6 = DateTime.Now; predictMC.R1(dao, currentSchedule, r.nbR1, UCA, lstGAP); DateTime endC6 = DateTime.Now; int time_Seconds_CLC6 = Convert.ToInt32((endC6 - startC6).TotalSeconds); //// C7 - NGO DateTime startC7 = DateTime.Now; setRCPurchasedItems(dao, currentSchedule, r.nbR2, lstGAP); DateTime endC7 = DateTime.Now; int time_Seconds_CLC7 = Convert.ToInt32((endC7 - startC7).TotalSeconds); //// C8 - MC DateTime startC8 = DateTime.Now; predictMC.R3(dao, currentSchedule, r.nbR3, UCA, lstGAP); DateTime endC8 = DateTime.Now; int time_Seconds_CLC8 = Convert.ToInt32((endC8 - startC8).TotalSeconds); //// C9 - MC DateTime startC9 = DateTime.Now; predictMC.R4(dao, currentSchedule, r.paramR4, UCA, lstGAP); DateTime endC9 = DateTime.Now; int time_Seconds_CLC9 = Convert.ToInt32((endC9 - startC9).TotalSeconds); ////Get R1R4 for new users DateTime startR1R4NewUsers = DateTime.Now; predictMC.R1R4_FOR_NEW_USERS(dao, currentSchedule, UCA); DateTime endR1R4NewUsers = DateTime.Now; int time_second_R1R4NewUsers = Convert.ToInt32((endR1R4NewUsers - startR1R4NewUsers).TotalSeconds); //GetPrice dao.GetPrice(); Console.WriteLine("FINISH"); // build statistic log List<string[]> lstStatic = dao.getStaticsData(); foreach (string[] statics in lstStatic) { schedule.Log += statics[0] + statics[1] + ". "; } schedule.Log += "Time to find LRS01 : " + time_Seconds_CLC6.ToString() + ". "; schedule.Log += "Time to find LRS02 : " + time_Seconds_CLC7.ToString() + ". "; schedule.Log += "Time to find LRS03 : " + time_Seconds_CLC8.ToString() + ". "; schedule.Log += "Time to find LRS04 : " + time_Seconds_CLC9.ToString() + ". "; schedule.Log += "Time to find recommendations for new clients : " + time_second_R1R4NewUsers.ToString() + ". "; schedule.Log += "System successfully stopped at " + DateTime.Now.ToString(); dao.updateRecommdationSchedule(schedule); dao.commitTransaction(); } catch (Exception ex) { dao.rollbackTransaction(); throw ex; } }
public Dictionary<string, double> getUCA(Predict_DAO_MC dao) { Dictionary<string, double> lstUCA = new Dictionary<string, double>(); try { lstUCA = dao.getUCA(); } catch (Exception) { lstUCA = null; } return lstUCA; }
public List<QTY_GAP> UpdateQTYGap(Predict_DAO_MC a, List<ADDGAP> list) { List<QTY_GAP> lst = new List<QTY_GAP>(); try { a.UpdateGAP(list); lst = a.GetGAP(); } catch (Exception) { throw; } return lst; }
//--------------------------------------------------------------------------------------- //This function computes the Confident Matrix and Weight Matrix, forllowing the formulars //Created by Vuong Minh Tuan //Corrected by MC. NGUYEN 21.10.2014. //--------------------------------------------------------------------------------------- public void ComputeConfident(Predict_DAO_MC dao) { dao.CLEAN_CONF_Matrix(); dao.CLEAN_WEIG_Matrix(); List<string> list_ClusterID = dao.getAllClusterID(); foreach (var item in list_ClusterID) { List<Transac> u_transacs = dao.getTransac_ForMatrix_ByClusterID_V2(item); if (u_transacs.Count > 0) { // Get QuantityMatrix - MC OK Dictionary<string, int> QM_dic_users = new Dictionary<string, int>(); Dictionary<string, int> QM_dic_items = new Dictionary<string, int>(); double[][] QuantityMatrix = Util.getQuantityMatrix_FromTransac_ByMetaItemID(u_transacs, out QM_dic_users, out QM_dic_items); if (QuantityMatrix[0].Length > 1) { // Compute Support One Item Matrix - MC OK double[] S = new double[QuantityMatrix[0].Length]; for (int j = 0; j < QuantityMatrix[0].Length; j++) { double count = 0.0; for (int i = 0; i < QuantityMatrix.Length; i++) if (QuantityMatrix[i][j] > 0) count++; S[j] = count; } // Compute Support Matrix - MC OK double[][] SupportMatrix = new double[QuantityMatrix[0].Length][]; for (int i = 0; i < QuantityMatrix[0].Length; i++) SupportMatrix[i] = new double[QuantityMatrix[0].Length]; for (int i = 0; i < QuantityMatrix.Length; i++) { for (int j = 0; j < QuantityMatrix[0].Length; j++) for (int j2 = 0; j2 < QuantityMatrix[0].Length; j2++) if (QuantityMatrix[i][j] > 0 & QuantityMatrix[i][j2] > 0 & j != j2) SupportMatrix[j][j2]++; } // Compute CONF Matrix - MC OK double[][] CONF = new double[QuantityMatrix[0].Length][]; for (int i = 0; i < QuantityMatrix[0].Length; i++) CONF[i] = new double[QuantityMatrix[0].Length]; for (int i = 0; i < QuantityMatrix[0].Length; i++) { for (int j = 0; j < QuantityMatrix[0].Length; j++) if (i == j) CONF[i][j] = 1.0; else if (S[i] > 0) CONF[i][j] = SupportMatrix[i][j] / S[i]; } // Compute WEIG Matrix - MC OK double[][] WEIG = new double[QuantityMatrix[0].Length][]; for (int i = 0; i < QuantityMatrix[0].Length; i++) WEIG[i] = new double[QuantityMatrix[0].Length]; for (int i = 0; i < QuantityMatrix[0].Length; i++) { for (int j = 0; j < QuantityMatrix[0].Length; j++) if (i != j) WEIG[i][j] = computeWEIG(i, j, SupportMatrix, QuantityMatrix); } // Save CONF Matrix - MC - OK for (int i = 0; i < CONF.Length; i++) for (int j = 0; j < CONF[0].Length; j++) if (CONF[i][j] > 0) { MatrixItem matrixItem = new MatrixItem(); matrixItem.Row = Util.FindKeyByValue(QM_dic_items, i); matrixItem.Column = Util.FindKeyByValue(QM_dic_items, j); matrixItem.Cell = CONF[i][j]; matrixItem.ClusterID = item; dao.setCONF_Matrix(matrixItem); } // Save WEIG Matrix for (int i = 0; i < WEIG.Length; i++) for (int j = 0; j < WEIG[0].Length; j++) if (WEIG[i][j] > 0) { MatrixItem matrixItem = new MatrixItem(); matrixItem.Row = Util.FindKeyByValue(QM_dic_items, i); matrixItem.Column = Util.FindKeyByValue(QM_dic_items, j); matrixItem.Cell = WEIG[i][j]; matrixItem.ClusterID = item; dao.setWEIG_Matrix(matrixItem); } } } } }
//---------------------------------------------------------------------------------------------- //This function gives R3 AND QUANTITY (with a number of recommendations for each user as input) //Created by MC. NGUYEN //Corrected by MC. NGUYEN, 22.10.2014. //---------------------------------------------------------------------------------------------- public List<Recommendation_Meta_Item> GetRecommendationR3(Predict_DAO_MC a, int nbR3) { List<Recommendation_Meta_Item> list = new List<Recommendation_Meta_Item>(); //Content is cleared by M.C. Nguyen 19.9.2015 return list; }
public List<Recommendation_Meta_Item> GetQuantityTraditionalUsersR3(Predict_DAO_MC a, List<Recommendation_Meta_Item> list, Dictionary<string, double> UCA) { double QTY; double M = 1; if (UCA.ContainsKey("MEANS_VALUE")) M = UCA["MEANS_VALUE"]; for (int i = 0; i < list.Count; i++) { QTY = a.GetQualtityTraditionalUser(list[i]); if (QTY != 0) list[i].Quantity = (int)(list[i].Quantity + QTY) / 2; //---------------------------------------- if (UCA.ContainsKey(list[i].UserID)) { list[i].Quantity = (int)list[i].Quantity * (UCA[list[i].UserID] / M); } } //-------------------- //a.commitTransaction(); return list; //} //catch (Exception ex) //{ // a.rollbackTransaction(); // throw ex; //} }
//--------------------------------------------------------------------------------------------- //This function call GetQualtityTraditionalUser to compute the quantity for each recommendations in the list //Created by: MC. NGUYEN //Corrected by: MC. NGUYEN 24.10.2014 //--------------------------------------------------------------------------------------------- public List<Recommendation_Meta_Item> GetQuantityTraditionalUsers(Predict_DAO_MC a, List<Recommendation_Meta_Item> list, Dictionary<string, double> UCA) { Int32 QTY; double M = 1; if (UCA.ContainsKey("MEANS_VALUE")) M = UCA["MEANS_VALUE"]; for (int i = 0; i < list.Count; i++) { QTY = a.GetQualtityTraditionalUser(list[i]); if (QTY > 0) list[i].Quantity = QTY; else list[i].Quantity = 1; if (UCA.ContainsKey(list[i].UserID)) { list[i].Quantity = (int)list[i].Quantity * (UCA[list[i].UserID] / M); } } return list; }
public List<Recommendation_Meta_Item> GetQuantityNewUsers(Predict_DAO_MC a, List<Recommendation_Meta_Item> list) { //Predict_DAO_MC a = new Predict_DAO_MC(); //List<U_I_Q> Cate_Item_QTY = new List<U_I_Q>(); //try //{ // a.beginTransaction(); list = a.GetAllQuantity(list); // a.commitTransaction(); return list; //} //catch (Exception ex) //{ // a.rollbackTransaction(); // throw ex; //} }
//THis function get a price of MetaItemID that correspondance with the quantity //---------------------------------------------------------------------------------- public double GetPrice(string MetaItemID, int QTY) { double Price = 0; Predict_DAO_MC a = new Predict_DAO_MC(); try { Price = a.GetPrice(MetaItemID, QTY); } catch (Exception) { throw; } return Price; }
public List<Recommendation_Meta_Item> GetRecommendations(string sql) { Predict_DAO_MC a = new Predict_DAO_MC(); try { a.beginTransaction(); List<Recommendation_Meta_Item> list = a.GetRecommendations(sql); a.commitTransaction(); return list; } catch (Exception ex) { a.rollbackTransaction(); throw ex; } }
public Settings GetRecommendationSeting(Predict_DAO_MC a) { Settings st = new Settings(); try { List<Recommendation_Setting> listCs = a.GetRecommendationSetting(); if (null != listCs && listCs.Count > 0) foreach (var item in listCs) { if (item.Key.Equals(ConstantValues.nb_R1)) { foreach (var cs_detail in item.Values) if (cs_detail.isDedault.Equals(true)) { st.nbR1 = Convert.ToInt32(cs_detail.Value.Trim()); break; } } else if (item.Key.Equals(ConstantValues.nb_R2)) { foreach (var cs_detail in item.Values) if (cs_detail.isDedault.Equals(true)) { st.nbR2 = Convert.ToInt32(cs_detail.Value.Trim()); break; } } else if (item.Key.Equals(ConstantValues.nb_R3)) { foreach (var cs_detail in item.Values) if (cs_detail.isDedault.Equals(true)) { st.nbR3 = Convert.ToInt32(cs_detail.Value.Trim()); break; } } else if (item.Key.Equals(ConstantValues.param_R4)) { foreach (var cs_detail in item.Values) if (cs_detail.isDedault.Equals(true)) { st.paramR4 = Convert.ToDouble(cs_detail.Value.Trim(), CultureInfo.CreateSpecificCulture("en-GB")); break; } } } } catch (Exception ex) { a.rollbackTransaction(); throw ex; } return st; }
//public List<Recommendation_Meta_Item> GetListRecommendC6_ForTraditionalUser() //{ // Predict_DAO_MC a = new Predict_DAO_MC(); // List<Recommendation_Meta_Item> list = new List<Recommendation_Meta_Item>(); // List<Recommendation_Meta_Item> RC = new List<Recommendation_Meta_Item>(); // try // { // a.beginTransaction(); // List<User> list_users_tra = a.getTraditionalUser_UnBlocked(); // foreach (User u in list_users_tra) // { // RC = a.GetRecommendC6_ForTraditionalUser(u, 1); // list.AddRange(RC); // } // a.commitTransaction(); // return list; // } // catch (Exception ex) // { // a.rollbackTransaction(); // throw ex; // } //} //---------------------------------------------------------------------------------------------- //This function calls GetRecommendC6_ForTraditionalUser from Predict_DAO_MC to give R1 //Created by MC. NGUYEN //Corrected by MC. NGUYEN, 22.10.2014 //Changed: 24.10.2014: the formule to calculate SCORE for each Meta Produit (based on Count(*)). //---------------------------------------------------------------------------------------------- public List<Recommendation_Meta_Item> getListRecommendation_R1_TraditionalUsers(Predict_DAO_MC a, int nbR1) { //Predict_DAO_MC a = new Predict_DAO_MC(); List<Recommendation_Meta_Item> list = new List<Recommendation_Meta_Item>(); List<Recommendation_Meta_Item> RC = new List<Recommendation_Meta_Item>(); List<string> lstCluster = new List<string>(); List<string> User_OfCluster = new List<string>(); //Settings r = GetRecommendationSeting(a); lstCluster = a.GetListClusterID(); //Check number of recommendations if (nbR1 <= 0) nbR1 = 1; //int i = 0; foreach (string cluster in lstCluster) { User_OfCluster = a.GetListUser_OfCluster(cluster); foreach (string u in User_OfCluster) { RC = a.GetRecommendC6_ForTraditionalUser(u, nbR1);//2 list.AddRange(RC); } } return list; }
//--------------------------------------------------------------------------------------- //This function computes the DISTANCE matrix and inserts it into the database //This is the distance between the two columns of the Rating Matrix //Created by Vuong Minh Tuan //Corrected all errors by MC. NGUYEN 21.10.2014. //--------------------------------------------------------------------------------------- public void ComputeDIST(Predict_DAO_MC dao) { dao.CLEAN_DIST_Matrix(); List<string> list_ClusterID = dao.getAllClusterID(); foreach (var item in list_ClusterID) { Dictionary<string, int> RM_dic_users = new Dictionary<string, int>(); Dictionary<string, int> RM_dic_items = new Dictionary<string, int>(); // Compute ratting matrix List<MatrixItem> lstRMI = dao.getRattingMatrixItem_ByClusterID(item); double[][] RattingMatrix = Util.toMatrix_MatrixItem(lstRMI, out RM_dic_users, out RM_dic_items); if (RattingMatrix.Length > 0 & RM_dic_items.Count > 1) { double[][] DIST = new double[RattingMatrix[0].Length][]; for (int i = 0; i < RattingMatrix[0].Length; i++) DIST[i] = new double[RattingMatrix[0].Length]; // Compute DIST Matrix for (int i1 = 0; i1 < RattingMatrix[0].Length - 1; i1++) for (int i2 = i1 + 1; i2 < RattingMatrix[0].Length; i2++) { double value = 0.0; for (int t = 0; t < RattingMatrix.Length; t++) value += Math.Pow(RattingMatrix[t][i1] - RattingMatrix[t][i2], 2); value = Math.Sqrt(value); DIST[i1][i2] = value; DIST[i2][i1] = value; } if (DIST.Length > 0) { double max = DIST[0][0]; // Find Max for (int i = 0; i < DIST.Length; i++) { double localMax = DIST[i].Max(); if (localMax > max) max = localMax; } // Standardization if (max != 0) { for (int i = 0; i < DIST.Length; i++) for (int j = 0; j < DIST[0].Length; j++) DIST[i][j] /= max; } // Save to Database for (int i = 0; i < DIST.Length; i++) for (int j = 0; j < DIST[0].Length; j++) if (DIST[i][j] > 0) { MatrixItem matrixItem = new MatrixItem(); matrixItem.Row = Util.FindKeyByValue(RM_dic_items, i); matrixItem.Column = Util.FindKeyByValue(RM_dic_items, j); matrixItem.Cell = DIST[i][j]; matrixItem.ClusterID = item; dao.setDIST_Matrix(matrixItem); } } } } }