Apparatus and method generating a path using classified distractions
An apparatus and method for generating a path, the apparatus including at least a processor; and a memory communicatively connected to the processor, the memory containing instructions configuring the processor to receive user data; track a user interest over a plurality of platforms, wherein tracking the user interest includes determining an interest level of a user on a platform of the plurality of platforms; identify a plurality of distractions as function of the user interest; classify the plurality of distractions to a plurality of categories including a productive category and a non-productive category; and generate a path for the user based on the classified plurality of distractions, wherein the path includes an activity related to a productive distraction.
1. An apparatus for generating a path using classified distractions, the apparatus comprising: at least a processor; and
a memory communicatively connected to the processor, the memory containing instructions configuring the processor to:
receive user data;
track a user interest over a plurality of platforms, wherein tracking the user interest comprises determining an interest level of a user on a platform of the plurality of platforms;
identify a plurality of distractions based on the user interest;
classify the plurality of distractions to a plurality of categories comprising a productive category and a non-productive category, wherein classifying the plurality of distractions further comprises:
receiving a productivity training data set comprising data correlating distractions to productivity classifications;
training a productivity classifier using the distraction training data set; and
outputting, using the distraction classifier, the productivity classification; and
generate a path for the user based on the classified plurality of distractions, wherein the path comprises an activity related to a productive distraction.
2. The apparatus of claim 1 , wherein the user data comprises a purpose of the user.
3. The apparatus of claim 2 , wherein the user data comprises a plurality of obligations related to the purpose of the user.
4. The apparatus of claim 1 , wherein tracking the user interest comprises receiving system logs from a user device.
5. The apparatus of claim 1 , wherein tracking the user interest comprises utilizing a mouse tracking method to track a movement of a cursor on user device.
6. The apparatus of claim 1 , wherein determining the interest level of the user further comprises determining an idle time of a user on a platform.
7. The apparatus of claim 1 , wherein generating the path for the user comprises:
generating a plurality of paths;
generating a utility score based on a usefulness for each path of the plurality of paths; and
ranking the plurality of paths based on the utility score.
8. The apparatus of claim 7 , wherein generating the utility score comprises:
receiving a utility training data set comprising data correlating a plurality of paths to a plurality of utility scores;
training a utility classifier using the utility training data set; and outputting, using the utility classifier, the utility score.
9. The apparatus of claim 1 , wherein generating the path for the user further comprises using a web crawler to populate a system database with a plurality of paths based on a productive distraction.
10. A method for generating a path using classified distractions, the method comprising:
receiving, by a computing device, user data;
tracking, by the computing device, a user interest over a plurality of platforms, wherein tracking the user interest comprises determining an interest level of a user on a platform of the plurality of platforms;
identifying, by the computing device, a plurality of distractions based on the user interest;
classifying, by the computing device, the plurality of distractions to a plurality of categories comprising a productive category and a non-productive category, wherein classifying the plurality of distractions further comprises:
receiving a productivity training data set comprising data correlating distractions to productivity classifications;
training a productivity classifier using the distraction training data set; and
outputting, using the distraction classifier, the productivity classification; and
generating by the computing device, a path for the user based on the classified plurality of distractions, wherein the path comprises an activity related to a productive distraction.
11. The method of claim 10 , wherein the user data comprises a purpose of the user.
12. The method of claim 11 , wherein the user data comprises a plurality of obligations related to the purpose of the user.
13. The method of claim 10 , wherein tracking the user interest comprises receiving system logs from a user device.
14. The method of claim 10 , wherein tracking the user interest comprises utilizing a mouse tracking method to track a movement of a cursor on user device.
15. The method of claim 10 , wherein determining the interest level of the user further comprises determining an idle time of a user on a platform.
16. The method of claim 10 , wherein generating the path for the user comprises:
generating a plurality of paths;
generating a utility score based on usefulness for each path of the plurality of paths; and
ranking the plurality of paths based on the utility score.
17. The method of claim 16 , wherein generating the utility score comprises:
receiving a utility training data set comprising data correlating a plurality of paths to a plurality of utility scores;
training a utility classifier using the utility training data set; and
outputting, using the utility classifier, the utility score.
18. The method of claim 10 , wherein generating the path for the user further comprises using a web crawler to populate a system database with a plurality of paths based on a productive distraction.