PROVIDING REASONS FOR CLASSIFICATION PREDICTIONS AND SUGGESTIONS

• US 20150142717A1
• Filed: 11/19/2013
• Published: 05/21/2015
• Est. Priority Date: 11/19/2013
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Guiver, John, Winn, John, Edelen, James, Sundelin, Tore
• Application Number:
  US14/084,554
• Publication Number:
  US 20150142717A1
• Time in Patent Office: Days
• US Class Current: 706/46
• CPC Class Codes: G06N 5/045 Explanation of inference; Explainable artificial intelligence [XAI]; Interpretable artificial intelligence
• CPC Class Codes: G06Q 10/107 Computer-aided management of electronic mailing [e-mailing]

Abstract

Technologies are generally provided for a prediction system to provide reasons corresponding to suggested classifications. The prediction system may predict classifications such as user actions on incoming messages to help users triage email, and may provide one or more reasons for classifications to a user. The prediction system may identify features of the message in order to make predictions about user interactions and to suggest an action to the user, where features may include characteristics of the email message such as sender identity. Presented reasons for a suggested action may convey observed features of the message that significantly contributed to the prediction decision, and were relatively unexpected compared to a typical item for a particular user.

Claims

1. A method executed at least in part in a computing device to provide reasons corresponding to a suggested classification of a prediction system, the method comprising:

receiving an incoming communication at a communication application;

predicting one or more classifications associated with the incoming communication;

determining one or more reasons for the predicted classification;

suggesting the predicted classification to a user; and

presenting the one or more reasons to the user along with the suggested classification.

2. The method of claim 1, further comprising:

extracting one or more features associated with the incoming communication.

3. The method of claim 2, wherein the one or more features include characteristics of the incoming communication including at least one from a set of:

communication type, a sender identity, recipient identities, identified key words or topics in a subject line or main body, an attachment type, attachment content, one or more previous contributions to the communication thread, document, or attachment by the user, and a message flag.

4. The method of claim 3, wherein predicting the one or more classifications comprises:

determining an absolute contribution of each of the one or more features, wherein the absolute contribution is a weighted sum of feature values.

5. The method of claim 4, wherein determining the one or more reasons comprises:

determining when a feature substantially contributes to a reason and is relatively unexpected compared to ordinary incoming communications associated with the user.

6. The method of claim 5, further comprising:

determining a relative contribution of each of the one or more extracted features.

7. The method of claim 6, further comprising:

determining the relative contribution based on a comparison of an expected contribution and the absolute contribution, wherein the expected contribution is computed based on an observed frequency of buckets associated with the one or more features.

8. The method of claim 7, wherein the buckets represent a set of discrete choices associated with each feature of the incoming communication.

9. The method of claim 1, further comprising:

generating a list of reasons that contribute to the suggested classification; and

mapping each observed feature to one of the reasons to which it contributes.

10. The method of claim 9, further comprising:

ranking each reason based on a calculated relative contribution value; and

sorting the list of the reasons in a descending order of relative contribution values.

11. The method of claim 10, further comprising:

presenting the reasons to the user where the relative contribution values for the one or more features contributing to the reasons exceed a predefined threshold value.

12. A computing device to provide reasons corresponding to a suggested classification of a prediction system, the computing device comprising:

a memory;

a processor coupled to the memory, the processor executing a prediction application, wherein the processor is configured to;

receive an incoming communication at a communication application;

extract one or more features from the incoming communication;

predict one or more classifications associated with the incoming communication;

determine one or more reasons for the predicted classification;

suggest the predicted classification to a user; and

present the one or more reasons to the user along with the suggested classification.

13. The computing device of claim 12, wherein the communication application facilitates one or more of:

an email exchange, an instant message exchange, a text message exchange, a social or gaming network invite, a social or gaming network update, a blog post, a forum post, a tweet, an audio communication, a video communication, an online meeting, data sharing, document sharing, and application sharing.

14. The computing device of claim 12, wherein the incoming communication is one or more an email, an instant message, a text message, a social or gaming network invite, a social or gaming network update, a blog post, a forum post, a tweet, an audio communication, a video communication, an online meeting communication, data sharing data, document sharing data, and application sharing data.

15. The computing device of claim 12, wherein the processor is further configured to:

determine an absolute contribution of each of the one or more features, wherein the absolute contribution is a weighted sum of feature values.

16. The computing device of claim 15, wherein the processor is configured to:

determine a relative contribution based on a comparison of an expected contribution and the absolute contribution, wherein the expected contribution is calculated based on an observed frequency of buckets associated with the one or more features.

17. The computing device of claim 15, wherein the processor is configured to:

merge two or more features together to contribute to a reason.

18. A computer-readable memory device with instructions stored thereon to provide reasons corresponding to a suggested classification of a prediction system, the instructions comprising:

receiving an incoming communication at a communication application;

extracting one or more features from the incoming communication;

predicting one or more classifications associated with the incoming communication;

determining one or more reasons for the predicted classification;

suggesting the predicted classification to a user; and

presenting the one or more reasons to the user along with the suggested classification, wherein the one or more reasons include when a feature substantially contributes to a reason and is relatively unexpected compared to ordinary incoming communications associated with the user.

19. The computer-readable memory device of claim 18, wherein the instructions further comprise:

determining an absolute contribution of each of the one or more features, wherein the absolute contribution is a weighted sum of feature values; and

determining a relative contribution based on a comparison of an expected contribution and the absolute contribution.

20. The computer-readable memory device of claim 19, wherein the instructions include:

mapping each observed feature to the reason to which it contributes;

ranking each reason based on the relative contribution value;

sorting the reasons in a descending order of relative contribution values; and

presenting a top reason having a highest relative contribution value to the user.