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Zied SELLAMI
priority-inbox
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07eeda09
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07eeda09
authored
Jan 31, 2019
by
Zied SELLAMI
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Update read me
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e258900e
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README.md
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07eeda09
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@@ -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
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@@ -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,
\n
first_name last_name\nDirector Tester",
"attachments" : [{
"file_size" : "243534",
"content_name" : "presentation.pdf",
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