Patent application EP17150734A (EP), filed 2017-01-09
Publication number: EP3229196A1
Title: BEHAVIOR PREDICTION
Abstract: [0001]    A method may include extracting feature information from a user history including multiple goal messages. Each of the multiple goal messages may include visual media and text, and may be associated with a goal indicated as completed. Extracting the feature information from the user history may include performing feature detection on the visual media of the multiple goal messages. The feature information from the user history may be analyzed for correlations between features and the completion indications of the associated goals. Feature information may be extracted from a generic goal message. A probability of a user indicating completion of a goal associated with the generic goal message may be determined based at least in part on the feature information from the generic goal message and the correlations between the features included in the multiple goal messages and the indications of the associated goals having been completed.
IPC codes: G06Q  30/    02            A I
G06Q  30/    06            A I
G06Q  50/    00            A I
Claims: number: 1
text: A method comprising:
number: 2
text: The method of claim 1, further comprising:
number: 3
text: The method of claim 2, wherein the one or more revised features of the personalized goal message is associated with an increase in the probability of the user indicating completion of the goal associated with the personalized goal message relative to the goal associated with the generic goal message.
number: 4
text: The method of any of claims 1 to 3, further comprising, in response to the probability of the user indicating completion of the goal associated with the generic goal message being at or above a probability threshold, delivering a personalized goal message equivalent to the generic goal message to a device associated with the user.
number: 5
text: The method of any of claims 1 to 4, wherein the performing the feature detection on the visual media of the plurality of goal messages includes detecting human faces.
number: 6
text: The method of any of claims 1 to 5, wherein the performing the feature detection on the visual media of the plurality of goal messages includes at least one of determining emotions of the visual media and determining emotions of detected human faces.
number: 7
text: The method of any of claims 1 to 6, wherein the extracting of the feature information from the user history further includes identifying positive words or phrases included in the text via text analysis.
number: 8
text: The method of any of claims 1 to 7, wherein the extracting of the feature information from the user history further includes identifying user features, including one or more of: a total number of goals indicated as completed by the user, and a theme preference of the user.
number: 9
text: A non-transitory computer-readable medium having encoded therein programing code executable by a processor to perform operations comprising the method according to any of claims 1 to 8.
number: 10
text: A system comprising:
number: 11
text: The system of claim 10, further comprising a personalization module for:
number: 12
text: The system of claim 10 or 11, wherein the performing the feature detection on the visual media of the plurality of messages includes at least one of determining emotions of the visual media and determining emotions of detected human faces.
number: 13
text: The system of any of claims claim 10 to 12, wherein the plurality of messages each further include text, and the extracting of the feature information from the user history further includes identifying positive words or phrases included in the text via text analysis.
number: 14
text: The system of any of claims 10 to 13, wherein the extracting of the feature information from the user history further includes identifying user features, including one or more of: a total number of events indicated as completed by the user, and a theme preference of the user.
Office action: search_report, dated 2017-10-11
Prior art cited: ref_id: - No relevant documents disclosed
ref_type: npl
severity: background
ref_id: [ ]     - No relevant documents disclosed
ref_type: npl
severity: background
Final disposition: pending (2017-10-11)