A computer-implemented system and method for predicting activity outcome based on user attention is provided. Sensor data is collected for a user, and an activity performed by a user is identified based on the sensor data. Features of the user are collected while performing the activity and a subject of focus of the user is determined based on the collected features. An outcome of the activity performed by the user is predicted based on the features and the determined subject of focus.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer-implemented system for predicting activity outcome based on user attention, comprising: sensor data collected for a user; and a server comprising a central processing unit, an input port to receive the sensor data, and an output port, wherein the central processing unit is configured to: identify an activity performed by a user based on the sensor data; collect features of the user while performing the activity; determine a subject of focus of the user based on the collected features; and predict an outcome of the activity performed by the user based on the features and the determined subject of focus. 2. A system according to claim 1, wherein the central processing unit is further configured to: select one or more references for the user based on the activity performed; provide the selected references to the user. 3. A system according to claim 1, wherein the central processing unit is further configured to: connect the user with an expert during performance of the activity. 4. A system according to claim 1, wherein the central processing unit is further configured to: predict the activity outcome by building models for a set of activities, building a classifier using the models, and classifying the activity with the predicted outcome via the classifier. 5. A system according to claim 1, wherein the central processing unit is further configured to: determine the activity by collecting contextual data of the user, identifying at least one low-level activity from the contextual data, comparing the identified low-level activities with activity models, wherein each activity model is associated with an activity, and selecting the activity associated with the activity model with the highest similarity to the identified low-level activities. 6. A system according to claim 1, wherein the central processing unit is further configured to: determine a recommendation for the user regarding completion of the activity based on the subject of focus; and provide the recommendation to the user. 7. A system according to claim 1, wherein the central processing unit is further configured to: detect a period of distraction of the user from performing the activity based on the features and the subject of focus. 8. A system according to claim 1, wherein the central processing unit is further configured to: collect the features via one of determining a distance of the user from a known object, determine a visual focus on an object, determine a visual focus on a person, and determine a focus on a piece of content. 9. A system according to claim 8, wherein the central processing unit is further configured to: monitor a Bluetooth beacon on one or more pieces of equipment; and determine the distance of the user from at least one of the equipment pieces based on the Bluetooth beacon. 10. A system according to claim 1, wherein the predicted outcome comprises one of successful completion and unsuccessful completion. 11. A computer-implemented method for predicting activity outcome based on user attention, comprising: identifying an activity performed by a user; collecting features of the user while performing the activity; determining a subject of focus of the user based on the collected features; and predicting an outcome of the activity performed by the user based on the features and the determined subject of focus. 12. A method according to claim 11, further comprising: selecting one or more references for the user based on the activity performed; providing the selected references to the user. 13. A method according to claim 11, further comprising: connecting the user with an expert during performance of the activity. 14. A method according to claim 11, wherein the activity outcome is predicted, comprising: building models for a set of activities; building a classifier using the models; and classifying the activity with the predicted outcome via the classifier. 15. A method according to claim 11, further comprising: determining the activity, comprising: collecting contextual data of the user; identifying at least one low-level activity from the contextual data; comparing the identified low-level activities with activity models, wherein each activity model is associated with an activity; and selecting the activity associated with the activity model with the highest similarity to the identified low-level activities. 16. A method according to claim 11, further comprising: determining a recommendation for the user regarding completion of the activity based on the subject of focus; and providing the recommendation to the user. 17. A method according to claim 11, further comprising: detecting a period of distraction of the user from performing the activity based on the features and the subject of focus. 18. A method according to claim 11, wherein collecting the features comprises one or more of: determining a distance of the user from a known object; determining a visual focus on an object; determining a visual focus on a person; and determining a focus on a piece of content. 19. A method according to claim 18, further comprising: monitoring a Bluetooth beacon on one or more pieces of equipment; and determining the distance of the user from at least one of the equipment pieces based on the Bluetooth beacon. 20. A method according to claim 11, wherein the predicted outcome comprises one of successful completion and unsuccessful completion.