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/* | |
Copyright (c) 2008 - Chris Buckley. | |
Permission is granted for use and modification of this file for | |
research, non-commercial purposes. | |
*/ | |
static int | |
te_calc_infap (const EPI *epi, const REL_INFO *rel_info, const RESULTS *results, | |
const TREC_MEAS *tm, TREC_EVAL *eval); | |
/* See trec_eval.h for definition of TREC_MEAS */ | |
TREC_MEAS te_meas_infAP = | |
{"infAP", | |
" Inferred AP\n\ | |
A measure that allows sampling of judgement pool: Qrels/results divided\n\ | |
into unpooled, pooled_but_unjudged, pooled_judged_rel,pooled_judged_nonrel.\n\ | |
My intuition of infAP:\n\ | |
Assume a judgment pool with a random subset that has been judged.\n\ | |
Calculate P at rel doc using only the judged higher retrieved docs,\n\ | |
then average in 0's from higher docs that were not in the judgment pool.\n\ | |
(Those in the pool but not judged are ignored, since they are assumed\n\ | |
to be relevant in the same proportion as those judged.)\n\ | |
Cite: 'Estimating Average Precision with Incomplete and Imperfect\n\ | |
Judgments', Emine Yilmaz and Javed A. Aslam. CIKM \n", | |
te_init_meas_s_float, | |
te_calc_infap, | |
te_acc_meas_s, | |
te_calc_avg_meas_s, | |
te_print_single_meas_s_float, | |
te_print_final_meas_s_float, | |
NULL, -1}; | |
static int | |
te_calc_infap (const EPI *epi, const REL_INFO *rel_info, const RESULTS *results, | |
const TREC_MEAS *tm, TREC_EVAL *eval) | |
{ | |
RES_RELS res_rels; | |
long j; | |
long nonrel_so_far, rel_so_far, pool_unjudged_so_far; | |
double inf_ap = 0.0; | |
if (UNDEF == te_form_res_rels (epi, rel_info, results, &res_rels)) | |
return (UNDEF); | |
nonrel_so_far = 0; | |
rel_so_far = 0; | |
pool_unjudged_so_far = 0; | |
for (j = 0; j < res_rels.num_ret; j++) { | |
if (res_rels.results_rel_list[j] == RELVALUE_NONPOOL) | |
/* document not in pool. Skip */ | |
continue; | |
if (res_rels.results_rel_list[j] == RELVALUE_UNJUDGED) { | |
/* document in pool but unjudged. */ | |
pool_unjudged_so_far++; | |
continue; | |
} | |
if (res_rels.results_rel_list[j] >= 0 && | |
res_rels.results_rel_list[j] < epi->relevance_level) { | |
nonrel_so_far++; | |
} | |
else { | |
/* Judged Rel doc */ | |
rel_so_far++; | |
/* Special case nonrel_so_far == 0 to avoid division by 0 */ | |
/* inf_ap */ | |
if (0 == j) | |
inf_ap += 1.0; | |
else { | |
double fj = (double) j; | |
inf_ap += 1.0 / (fj+1.0) + | |
(fj / (fj+1.0)) * | |
((rel_so_far-1+nonrel_so_far+pool_unjudged_so_far) / fj) * | |
((rel_so_far-1 + INFAP_EPSILON) / | |
(rel_so_far-1 + nonrel_so_far + 2 * INFAP_EPSILON)); | |
} | |
} | |
} | |
if (res_rels.num_rel) { | |
inf_ap /= res_rels.num_rel; | |
} | |
eval->values[tm->eval_index].value = inf_ap; | |
return (1); | |
} | |