public Boolean deleteAllRecommendedJob() { RecommendedJobManager mgr = new RecommendedJobManager(); return mgr.deleteAllRecommendedJob(); }
public bool ExecuteMainRoutine() { try { RecommendedJobManager recJobMgr = new RecommendedJobManager(); new Thread(() => { Thread.CurrentThread.IsBackground = true; bool result_delete = recJobMgr.deleteAllRecommendedJob(); }).Start(); JobManager jobMgr = new JobManager(); String[] job_list = jobMgr.selectExpressionNames(); //job_names double[] X = jobMgr.selectExpressionDifficulty(); //X double[,] new_X = new double[X.Length, 1]; for (int i = 0; i < X.Length; i++) { new_X[i, 0] = X[i]; } //////User Profile (just the user ID, I still need the user self rating) //////RecruiteeSvcImpl r = new RecruiteeSvcImpl(); RecruiteeManager recMgr = new RecruiteeManager(); String[] recruitee_names = recMgr.selectRecruiteeNames(); double[] recruitee_skill = recMgr.selectRecruiteeSkills(); UserProfile[] users_profile = new UserProfile[recruitee_skill.Length]; for (int i = 0; i < recruitee_skill.Length; i++) { users_profile[i] = new UserProfile("", 0); users_profile[i].UserID = recruitee_names[i]; users_profile[i].UserRating = recruitee_skill[i]; } //////new_Y ElasticManager elasticMgr = new ElasticManager(); double[,] Y = elasticMgr.SelectRatings(job_list, users_profile); ///////////// WRITING VARIABLES IN FILE //////////// //FromWebToFileManager file = new FromWebToFileManager(); //file.writeFiles(job_list, new_X, users_profile, Y); //////Object to Hold Task Parameters TaskDimensions task = new TaskDimensions(); task.num_features = new_X.GetLength(1); //1 is the number of columns task.num_jobs_init = job_list.Length; task.num_users_init = recruitee_names.Length; //////User number to start proccessing int user_number = 1; //////Load File System Service FileSystemManager fileSystemMgr = new FileSystemManager(); //////Creating a variable to write in a File the job recommendations and comparisons //////Load File Writer StreamWriter writeTextResult = fileSystemMgr.getResultStreamWriter(); StreamWriter writeTextAverages = fileSystemMgr.getAverageStreamWriter(); StreamWriter writeText = fileSystemMgr.getIdandAvgStreamWriter(); StreamWriter writeTextDiff = fileSystemMgr.getDifficultyStreamWriter(); double[] users_calculated_raitings = new double[task.num_users_init]; double total_rating_avg_system = 0; double total_similarity_avg_system = 0; double total_inaccuracy_system = 0; MatlabManager matlabMgr = new MatlabManager(); while (user_number <= task.num_users_init) { double[,] my_ratings = new double[task.num_jobs_init, 1]; double[,] new_Y = new double[task.num_jobs_init, task.num_users_init - 1]; double[,] R = new double[task.num_jobs_init, task.num_users_init - 1]; for (int i = 0; i < job_list.Length; i++) { int k = 0; for (int n = 0; n < users_profile.Length; n++) { if (n != (user_number - 1)) { new_Y[i, k] = Y[i, n]; if (Y[i, n] != 0) R[i, k] = 1; else R[i, k] = 0; k++; } else my_ratings[i, 0] = Y[i, n]; } } object[] res = matlabMgr.executeFilter(task, job_list, path_fix + "files", my_ratings, new_Y, R, new_X); // ////Each time creates a to be used to write the recommended jobs in a file List<TopJobData> mylist = fileSystemMgr.writeValuesToFile(writeTextResult, res, job_list, user_number, new_X); // ////Calculate Averages for Jobs for a User DataResult avgs = new DataResult(mylist, mylist.Count, users_profile[user_number - 1]); avgs.AverageForEachJob(); fileSystemMgr.writeAveragesToFile(avgs, writeTextAverages, users_profile[user_number - 1]); total_rating_avg_system += avgs.Rating_total_avg; total_similarity_avg_system += avgs.Percentage_total_avg; total_inaccuracy_system += avgs.Self_inaccuracy; // ////adding the list at the Dictionary for each user // ////ID and AVGs file writeText.WriteLine(users_profile[user_number - 1].UserID + "\t" + avgs.Rating_total_avg); users_calculated_raitings[user_number - 1] = avgs.Rating_total_avg; // ////writing in the difficulty file fileSystemMgr.writeDifficultyToFile(writeTextDiff, avgs); new Thread(() => { Thread.CurrentThread.IsBackground = true; ////used to insert recommended jobs for a user in the database bool result = elasticMgr.insertRecommenderJob(avgs); }).Start(); user_number++; } total_rating_avg_system /= task.num_users_init; total_similarity_avg_system /= task.num_users_init; total_inaccuracy_system /= task.num_users_init; ////writing some more global information fileSystemMgr.writeGlobalAveragesInformation(total_rating_avg_system, total_similarity_avg_system, total_inaccuracy_system, task, writeTextAverages, users_profile, users_calculated_raitings); //////closing the four files writeText.Close(); writeTextResult.Close(); writeTextAverages.Close(); writeTextDiff.Close(); return true; } catch (Exception ex) { return false; } }