Update paper link.

BWendy1 · Aug 7, 2017 · 22994f9 · 22994f9
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Showing 2 changed files with 14 additions and 7 deletions.
diff --git a/MST.c b/MST.c
@@ -712,6 +712,7 @@ void *TrainModelThread(void *id) {
         }
         else {
           real max_exp = -1000000000000;
+          real min_exp = 1000000000000;
           real max_p = -1;
           for (p = 0; p < syn0[target].num; ++p) {
             // calc the average embedding of several sememes for each sense
@@ -738,8 +739,15 @@ void *TrainModelThread(void *id) {
               max_exp = _exp[p]; 
               max_p = p;
             }
+            if (_exp[p] < min_exp) {
+              min_exp = _exp[p];
+            }
+          }
+          real gap_exp = max_exp - min_exp;
+          if (gap_exp >= 3.999) {
+            gap_exp = 3.999;
           }
-          total = 1.0;
+          total = pre_exp[(int)(gap_exp * 250.0)];
           // use the sense with max weight to represent a word
           for (p = 0; p < syn0[target].num; ++p) {
             if (p != max_p) {
@@ -783,7 +791,7 @@ void *TrainModelThread(void *id) {
               avg_num = 1.0 / (real)(syn0[target].meaning_word_cnt[p] - syn0[target].meaning_word_cnt[p - 1]);
             real *temp_mult = &(syn0[target].mult_sense_value[p * layer1_size]);
             for (c = 0; c < layer1_size; ++c) {
-              mult_part2[c] = mult_part[c] * (temp_mult[c] - attention[c]) * avg_num;
+              mult_part2[c] = mult_part[c] * temp_mult[c] * avg_num;
             }
             for (q = (p == 0 ? 0 : syn0[target].meaning_word_cnt[p - 1]); q < syn0[target].meaning_word_cnt[p]; ++q) {
               real *temp = &(meaning_syn[syn0[target].meaning_word_rank[q] * layer1_size]);
@@ -794,13 +802,12 @@ void *TrainModelThread(void *id) {
             break;
           }
 
+          for (c = 0; c < layer1_size; ++c)
+              mult_part[c] = 0;
           for (p = 0; p < syn0[target].num; ++p) {
-            if (_exp[p] < 0.1)
-              continue;
             real *temp_mult = &(syn0[target].mult_sense_value[p * layer1_size]);
             for (c = 0; c < layer1_size; ++c)
-              mult_part[c] = avg_meaning[p * layer1_size + c] * (temp_mult[c] - attention[c]);
-            break;
+              mult_part[c] += avg_meaning[p * layer1_size + c] * temp_mult[c];
           }
           for (p = 0; p < layer1_size; ++p)
             mult_part[p] *= g * syn1neg[p + l1] * cnt;

diff --git a/README.md b/README.md
@@ -34,7 +34,7 @@ The annotation information is for the four files ``SSA.c/MST.c/SAC.c/SAT.c``. An
 
 ## Revise
 
-I'm sorry that we found bugs in programs. We have revised them. The new experiment results will be released on GitHub and new version of paper will be given. 
+I'm sorry that we found bugs in programs. We have revised them. The new experiment results are released on GitHub and [new version of paper](http://thunlp.org/~lzy/publications/acl2017_sememe.pdf) is given. 
 
 #### Word Similarity