Presentation of organized personal and public data using communication mediums
View Patent ↗Systems, methods and computer program products for providing information associated with an attachment (e.g., attachment received through an instant message system, online collaboration tool, electronic message and the like). A sidebar may allow a user to view comprehensive profile and content information associated with the attachment using an attachment information viewer. The sidebar also may allow the user to switch between a message attachment information view (e.g., to facilitate browsing of the document or attachment) and a person profile information view (e.g., to facilitate browsing of personal or public data).
1. A method comprising:
identifying a time period in which first messages are to be monitored;
monitoring one or more user actions of a user associated with the first messages, wherein the first messages are received from subjects, and the first messages each include at least one attachment;
developing, by a processor, training data based on the one or more monitored user actions;
learning, by the processor and based on the training data, types of responses of the user;
analyzing the at least one attachment for each of the first messages including parsing the at least one attachment to locate text;
inferring preferences of the subjects based on the analyzing to provide subject profiles;
receiving, by the processor, a second message subsequent to the first messages;
predicting, by the processor, based on learning the types of responses of the user, a first type of response to the second message;
providing, by the processor, a template for preparing a reply to the second message, wherein providing the template is based on predicting the first type of response, and wherein content of the template is based on at least one of the subject profiles; and
presenting, by a display, the template to the user, wherein the template is presented for modification of the reply prior to sending the reply to the second message, and the modification is made in response to user input received from the user in a messaging client.
2. The method of claim 1 , wherein the monitoring one or more user actions of the user associated with the first messages includes:
determining which of the first messages are important to the user based on the one or more monitored user actions; and
identifying one or more characteristics associated with the determined messages.
3. The method of claim 2 , wherein the determining which of the first messages are important to the user based on the one or more monitored user actions includes:
querying the user as to which of the first messages are important.
4. The method of claim 3 , wherein the messaging client executes on a mobile device associated with the user, and wherein the querying the user includes sending a short message service (SMS) text to the mobile device.
5. The method of claim 2 , wherein the developing training data based on the one or more monitored user actions includes developing training data based on the one or more identified characteristics.
6. A non-transitory computer-readable medium having instructions stored thereon, which, when executed by a processor, cause the processor to perform operations comprising:
identifying a time period in which first messages are to be monitored;
monitoring one or more user actions of a user associated with the first messages, wherein the first messages are received from subjects, and the first messages each include at least one attachment;
developing training data based on the one or more monitored user actions;
learning, based on the training data, types of responses of the user;
analyzing the at least one attachment for each of the first messages including parsing the at least one attachment to locate text;
inferring preferences of the subjects based on the analyzing to provide subject profiles;
receiving a second message subsequent to the first messages;
predicting, based on learning the types of responses of the user, a first type of response to the second message;
providing a template for preparing a reply to the second message, wherein providing the template is based on predicting the first type of response, and wherein content of the template is based on at least one of the subject profiles; and
presenting, by a display, the template to the user, wherein the template is presented for modification of the reply prior to sending the reply to the second message, and the modification is made in response to user input received from the user in a messaging client.
7. The non-transitory computer-readable medium of claim 6 , wherein the monitoring one or more user actions of the user associated with the first messages includes:
determining which of the first messages are important to the user based on the one or more monitored user actions; and
identifying one or more characteristics associated with the determined messages.
8. The non-transitory computer-readable medium of claim 7 , wherein the determining which of the first messages are important to the user based on the one or more monitored user actions includes:
querying the user as to which of the first messages are important.
9. The non-transitory computer-readable medium of claim 8 , wherein the messaging client executes on a mobile device associated with the user, and wherein the querying the user includes sending a short message service (SMS) text to the mobile device.
10. The non-transitory computer-readable medium of claim 7 , wherein the developing training data based on the one or more monitored user actions includes developing training data based on the one or more identified characteristics.
11. A system comprising:
a processor executing a messaging client;
a display configured to present templates for modification based on user input to the messaging client; and
memory storing instructions configured to instruct the processor to:
identify a time period in which first messages are to be monitored;
monitor one or more user actions of a user associated with the first messages, wherein the first messages are received from subjects, and the first messages each include at least one attachment;
develop training data based on the one or more monitored user actions;
learn, based on the training data, types of responses of the user;
analyze the at least one attachment for each of the first messages including parsing the at least one attachment to locate text;
infer preferences of the subjects based on the analyzing to provide subject profiles;
receive a second message subsequent to the first messages;
predict, based on learning the types of responses of the user, a first type of response to the second message;
provide a first template for preparing a reply to the second message, wherein providing the template is based on predicting the first type of response, and wherein content of the template is based on at least one of the subject profiles; and
present, by the display, the first template to the user, wherein the first template is presented for modification of the reply prior to sending the reply to the second message, and the modification is made in response to user input received from the user in the messaging client.
12. The system of claim 11 , wherein the monitoring one or more user actions of the user associated with the first messages includes:
determining which of the first messages are important to the user based on the one or more monitored user actions; and
identifying one or more characteristics associated with the determined messages.
13. The system of claim 12 , wherein the determining which of the first messages are important to the user based on the one or more monitored user actions includes:
querying the user as to which of the first messages are important.
14. The system of claim 13 , wherein the messaging client executes on a mobile device associated with the user, and wherein the querying the user includes sending a short message service (SMS) text to the mobile device.
15. The system of claim 12 , wherein the developing training data based on the one or more monitored user actions includes developing training data based on the one or more identified characteristics.