optimize investment mapping algorithm

core/data_mapping.py

@@ -283,16 +283,25 @@ class DataMapping:
                 doc_compare_mapping = self.doc_fund_class_mapping[
                     self.doc_fund_class_mapping["FundId"] == parent_id
                 ]
-                doc_compare_name_list = (
+                if len(doc_compare_mapping) == 0:
-                    doc_compare_mapping["ShareClassName"].unique().tolist()
+                    doc_compare_name_list = self.doc_share_name_list
-                )
+                    doc_compare_mapping = self.doc_fund_class_mapping
+                else:
+                    doc_compare_name_list = (
+                        doc_compare_mapping["ShareClassName"].unique().tolist()
+                    )
 
                 provider_compare_mapping = self.provider_fund_class_mapping[
                     self.provider_fund_class_mapping["FundId"] == parent_id
                 ]
-                provider_compare_name_list = (
+                if len(provider_compare_mapping) == 0 or \
-                    provider_compare_mapping["ShareClassName"].unique().tolist()
+                    len(provider_compare_mapping) < len(doc_compare_mapping):
-                )
+                    provider_compare_name_list = doc_compare_name_list
+                    provider_compare_mapping = doc_compare_mapping
+                else:
+                    provider_compare_name_list = (
+                        provider_compare_mapping["ShareClassName"].unique().tolist()
+                    )
             else:
                 doc_compare_name_list = self.doc_share_name_list
                 doc_compare_mapping = self.doc_fund_class_mapping

main.py

@@ -574,8 +574,8 @@ def test_data_extraction_metrics():
 
 
 def test_mapping_raw_name():
-    doc_id = "382366116"
+    doc_id = "445102363"
-    raw_name = "SPARINVEST SICAV - ETHICAL EMERGING MARKETS VALUE EUR I"
+    raw_name = "Danske Invest SICAV Global Portfolio Solution – Defensive Class X"
     output_folder = r"/data/emea_ar/output/mapping_data/docs/by_text/"
     data_mapping = DataMapping(
         doc_id,
@@ -692,16 +692,21 @@ if __name__ == "__main__":
         "394778487",
         "401684600",
         "402113224",
-        "402181770"
+        "402181770",
+        "402397014",
+        "405803396",
+        "445102363",
+        "445256897",
+        "448265376"
     ]
     # special_doc_id_list = check_mapping_doc_id_list
     special_doc_id_list = check_db_mapping_doc_id_list
-    special_doc_id_list = ["402397014"]
+    # special_doc_id_list = ["391736837"]
     output_mapping_child_folder = r"/data/emea_ar/output/mapping_data/docs/"
     output_mapping_total_folder = r"/data/emea_ar/output/mapping_data/total/"
     re_run_extract_data = False
     re_run_mapping_data = True
-    force_save_total_data = False
+    force_save_total_data = True
 
     extract_ways = ["text"]
     for extract_way in extract_ways:

utils/biz_utils.py

@@ -169,6 +169,7 @@ def get_most_similar_name(text: str,
                 text_currency = get_currency_from_text(share_name)
         
         # logger.info(f"Source text: {text}, candidate names count: {len(copy_name_list)}")
+        same_max_similarity_name_list = []
         for full_name, copy_name in zip(name_list , copy_name_list):
             copy_name = remove_special_characters(copy_name)
             copy_name = split_words_without_space(copy_name)
@@ -219,8 +220,20 @@ def get_most_similar_name(text: str,
                                 continue
                 max_similarity = similarity
                 max_similarity_full_name = full_name
+                same_max_similarity_name_list = []
+            elif matching_type == "fund" and max_similarity > 0 and max_similarity == similarity:
+                if full_name is not None and max_similarity_full_name is not None and \
+                    len(full_name.split()) > len(max_similarity_full_name.split()):
+                    max_similarity_full_name = full_name
+                    same_max_similarity_name_list = []
+                else:
+                    if full_name is not None:
+                        same_max_similarity_name_list.append(full_name)
             if max_similarity == 1:
                 break
+        # if there are multiple names with the same similarity, return None
+        if len(same_max_similarity_name_list) > 0:
+            return None, 0.0
         if max_similarity < 0.35:
             return None, max_similarity
         return max_similarity_full_name, max_similarity
@@ -561,6 +574,8 @@ def replace_abbrevation(text: str):
             new_text_splits.append('Advantage')
         elif split.lower() in ['hdg', 'hgd', 'hdg.', 'hgd.', '(h)']:
             new_text_splits.append('Hedged')
+        elif split.lower() in ['unhgd']:
+            split = ""
         elif split.lower() in ['cl', 'cl.']:
             new_text_splits.append('Class')
         elif split.lower() in ['ser', 'ser.']: