The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Apr. 19, 2022
Filed:
Sep. 30, 2020
Microsoft Technology Licensing, Llc, Redmond, WA (US);
Christian Wilhelm Kurt Byza, San Francisco, CA (US);
Jeffrey William Pasternack, Fremont, CA (US);
Haowen Ning, Sunnyvale, CA (US);
Pujita Mathur, San Francisco, CA (US);
Yizhou Pan, San Francisco, CA (US);
Ngoc M. Vu, San Francisco, CA (US);
Akshaya Subbaraya Bhat, San Francisco, CA (US);
Arya Ghatak Choudhury, Sunnyvale, CA (US);
Jia Liu, Sunnyvale, CA (US);
Neil Cruz Pomerleau, Mountain View, CA (US);
Howard Mario Narvaez, Milpitas, CA (US);
Kelly K. Hosokawa, Alameda, CA (US);
Ryan A. Espiritu, Los Altos, CA (US);
Microsoft Technology Licensing, LLC, Redmond, WA (US);
Abstract
Methods are presented for classifying responses to communications. One method includes presenting, in a first user interface (UI), a message from a sender to a recipient requesting a response. The first UI includes response options of a first classification, a second classification, and an entry field for entering a free text message. Another operation is for receiving a recipient response with a selection of: (a) the first or the second button and (b) the free text message entered in the text entry field. The method further includes generating a featurized recipient response based on the free text message and the selection. An acceptance machine-learning (ML) model calculates a classification value of the recipient response from a set of possible classification values based on the featurized recipient response. The method further includes presenting, in a second UI for the sender, an indicator for the message and the calculated classification value.