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| /* | |
| Copyright (c) 2008 - Chris Buckley. | |
| Permission is granted for use and modification of this file for | |
| research, non-commercial purposes. | |
| */ | |
| double log2(double x); | |
| static int | |
| te_calc_ndcg_cut (const EPI *epi, const REL_INFO *rel_info, | |
| const RESULTS *results, const TREC_MEAS *tm, TREC_EVAL *eval); | |
| static long long_cutoff_array[] = {5, 10, 15, 20, 30, 100, 200, 500, 1000}; | |
| static PARAMS default_ndcg_cutoffs = { | |
| NULL, sizeof (long_cutoff_array) / sizeof (long_cutoff_array[0]), | |
| &long_cutoff_array[0]}; | |
| /* See trec_eval.h for definition of TREC_MEAS */ | |
| TREC_MEAS te_meas_ndcg_cut = | |
| {"ndcg_cut", | |
| " Normalized Discounted Cumulative Gain at cutoffs.\n\ | |
| Compute a traditional nDCG measure according to Jarvelin and\n\ | |
| Kekalainen (ACM ToIS v. 20, pp. 422-446, 2002) at cutoffs.\n\ | |
| See comments for ndcg.\n\ | |
| Gain values are the relevance values in the qrels file. For now, if you\n\ | |
| want different gains, change the qrels file appropriately.\n\ | |
| Cutoffs must be positive without duplicates\n\ | |
| Default params: -m ndcg_cut.5,10,15,20,30,100,200,500,1000\n\ | |
| Based on an implementation by Ian Soboroff\n", | |
| te_init_meas_a_float_cut_long, | |
| te_calc_ndcg_cut, | |
| te_acc_meas_a_cut, | |
| te_calc_avg_meas_a_cut, | |
| te_print_single_meas_a_cut, | |
| te_print_final_meas_a_cut, | |
| (void *) &default_ndcg_cutoffs, -1}; | |
| static int | |
| te_calc_ndcg_cut (const EPI *epi, const REL_INFO *rel_info, | |
| const RESULTS *results, const TREC_MEAS *tm, TREC_EVAL *eval) | |
| { | |
| long *cutoffs = (long *) tm->meas_params->param_values; | |
| long cutoff_index = 0; | |
| RES_RELS res_rels; | |
| double gain, sum; | |
| double ideal_dcg; /* ideal discounted cumulative gain */ | |
| long cur_lvl, lvl_count; | |
| long i; | |
| if (UNDEF == te_form_res_rels (epi, rel_info, results, &res_rels)) | |
| return (UNDEF); | |
| sum = 0.0; | |
| for (i = 0; i < res_rels.num_ret; i++) { | |
| if (i == cutoffs[cutoff_index]) { | |
| /* Calculate previous cutoff threshold. | |
| Note i guaranteed to be positive by init_meas */ | |
| eval->values[tm->eval_index + cutoff_index].value = sum; | |
| if (++cutoff_index == tm->meas_params->num_params) | |
| break; | |
| if (epi->debug_level > 0) | |
| printf("ndcg_cut: cutoff %ld dcg %6.4f\n", i, sum); | |
| } | |
| gain = res_rels.results_rel_list[i]; | |
| if (gain > 0) { | |
| /* Note: i+2 since doc i has rank i+1 */ | |
| sum += gain / log2((double) (i+2)); | |
| if (epi->debug_level > 1) | |
| printf("ndcg_cut:%ld %3.1f %6.4f\n", i, gain, sum); | |
| } | |
| } | |
| /* calculate values for those cutoffs not achieved */ | |
| while (cutoff_index < tm->meas_params->num_params) { | |
| eval->values[tm->eval_index + cutoff_index].value = sum; | |
| if (epi->debug_level > 0) | |
| printf("ndcg_cut: cutoff %ld dcg %6.4f\n", | |
| cutoffs[cutoff_index], sum); | |
| cutoff_index++; | |
| } | |
| /* Calculate ideal discounted cumulative gain for this topic, and | |
| normalize previous sum by it */ | |
| cutoff_index = 0; | |
| cur_lvl = res_rels.num_rel_levels - 1; | |
| lvl_count = 0; | |
| ideal_dcg = 0.0; | |
| for (i = 0; 1; i++) { | |
| lvl_count++; | |
| while (cur_lvl > 0 && lvl_count > res_rels.rel_levels[cur_lvl]) { | |
| cur_lvl--; | |
| lvl_count = 1; | |
| } | |
| if (cur_lvl == 0) | |
| break; | |
| if (i == cutoffs[cutoff_index]) { | |
| /* Calculate previous cutoff threshold. | |
| Note i guaranteed to be positive by init_meas */ | |
| if (ideal_dcg > 0.0) | |
| eval->values[tm->eval_index + cutoff_index].value /= ideal_dcg; | |
| if (epi->debug_level > 0) | |
| printf("ndcg_cut: cutoff %ld idcg %6.4f\n", i, ideal_dcg); | |
| if (++cutoff_index == tm->meas_params->num_params) | |
| break; | |
| } | |
| gain = cur_lvl; | |
| ideal_dcg += gain / (double) log2((double)(i + 2)); | |
| if (epi->debug_level > 0) | |
| printf("ndcg_cut:%ld %ld %3.1f %6.4f\n",i, cur_lvl, gain,ideal_dcg); | |
| } | |
| /* calculate values for those cutoffs not achieved */ | |
| while (cutoff_index < tm->meas_params->num_params) { | |
| if (ideal_dcg > 0.0) | |
| eval->values[tm->eval_index + cutoff_index].value /= ideal_dcg; | |
| if (epi->debug_level > 0) | |
| printf("ndcg_cut: cutoff %ld idcg %6.4f\n", | |
| cutoffs[cutoff_index], ideal_dcg); | |
| cutoff_index++; | |
| } | |
| return (1); | |
| } | |