Update read me

README.md

@@ -14,11 +14,11 @@ A small dataset of **604** emails was annotated manually (**234** important emai
 Remember that this AI approach are not based on Machine Learning but only on generic rules to compute a priority for an email.
 
 **The next table resume the obtained results:**
-|Email Category|Precision|Recall|Fmeasure|
-|--|--|--|--|
-|Important|81.90%|73.50%|77.47%|
-|To_Read|25.39%|65.30%|36.57%|
-|Notification|99.62%|83.17%|90.66%|
+|Email Category	|Precision	|Recall	|Fmeasure	|
+|--	|--	|--	|--	|
+|Important	|81.90%	|73.50%	|77.47%	|
+|To_Read	|25.39%	|65.30%	|36.57%	|
+|Notification	|99.62%	|83.17%	|90.66%	|
   
 
 # Running the service with Docker
@@ -75,7 +75,7 @@ Sample of json file:
   "Date" : "Mon, 28 Jan 2019 07:56:43 +0000",
   "in-Reply-To" : "messageId_in_reply_to",
   "subject" : "IMPORTANT: Testing The Priority Inbox",
-  "body" : "\nDear, \n\n this a test of the priority inbox\n regards, first_name last_name of to1\nDirector Tester",
+  "body" : "\nDear, \n\n this a test of the priority inbox\n regards,\nfirst_name last_name\nDirector Tester",
   "attachments" : [{
     "file_size" : "243534",
     "content_name" : "presentation.pdf",