Analyzing and Predicting Task Reminders

Analyzing and Predicting Task RemindersDavid Graus, Paul N. Bennett, Ryen W. White, Eric Horvitz

Analyzing and Predicting Task RemindersWed 13 July 2016, UMAP 2016 2


When would you like to be reminded?

Alright, remind you to do the laundryat 12:00pm on Sunday, is that right?

Great, I’ll remind you!

Sunday at noon.

Remind me to do the laundry.

Yes.





Sunday at noon.


Yes.




Sunday at noon.


Yes.





Sunday at noon.


Yes.




Sunday at noon.


Yes.




Sunday at noon.


Yes.





Sunday at noon.


Yes.




Sunday at noon.


Yes.




Sunday at noon.


Yes.




Sunday at noon.


Yes.





Sunday at noon.


Yes.




Sunday at noon.


Yes.




Sunday at noon.


Yes.




Sunday at noon.


Yes.




Sunday at noon.


Yes.





Sunday at noon.


Yes.




Sunday at noon.


Yes.




Sunday at noon.


Yes.




Sunday at noon.


Yes.




Sunday at noon.


Yes.




Sunday at noon.


Yes.


Research questions


Research questions

1. Is there a body of common tasks that underlie the reminder creation process?


Research questions


2. Can we identify patterns in the times at which people create reminders, and, via notification times, when the associated tasks are to be executed?


Research questions


2. Can we identify patterns in the times at which people create reminders, and, via notification times, when the associated tasks are to be executed?

3. Can we predict when certain tasks are most likely to happen?


Is there a body of common tasks that underlie the reminder creation process?



• Common reminder structure: • “Remind me to <verb> <object>” • take out laundry • call mom • pay bills




• Identify frequent verb/object-pairs in 2-month sample (~950k reminders)




• Identify frequent verb/object-pairs in 2-month sample (~950k reminders)

• Manually group them into tasks


~60% of reminders start with one of these (52) verbs

take eathave send email textcall tell setmake scheduleturn on turn off

checkleave come be go tostop by take out feed clean wash charge do write

change cancel order renew book mail submit fill out print pay wake set


Manual labeling

Ò Dimensions; Ò Interruption vs. continuation of user activity Ò Context of task (home, work, on the go) Ò (Expected) duration of task Ò Impact on user “availability” Ò …


common tasks that underlie the reminder creation process


Go somewhere Switch context Run errand





Go somewhere

Chores

Switch context Run errand

Recurring Standalone




Go somewhere

Chores



Go somewhere

Chores

Communicate



General Coordinate




Go somewhere

Chores



Go somewhere

Chores

Communicate



General Coordinate

Go somewhere

Chores

Communicate

Manage Ongoing

External Process

Manage Ongoing

User Activity

Eat/Consume



General Coordinate

StartPrepare Stop


RQ2: Can we identify patterns in the reminder creation process?



Ò Creation time (CT) Ò When user creates the reminder (remembers task)




Ò Notification time (NT) Ò When reminder is set to trigger (executes task)





Ò Time delta (NT – CT) Ò How far task is planned in advance





Ò Time delta (NT – CT) Ò How far task is planned in advance

Ò Text/task description


00:00am–04:00am

04:00am–08:00am

08:00am–12:00pm

12:00pm–4:00pm

4:00pm–8:00pm

8:00pm–0:00am

SunMonTueWedThuFriSat



1. Aggregate 2. Per task type 3. By Creation Time and Terms (in task description)


Creation times Notification times

1: Aggregate patterns (across all tasks)


Findings: Aggregate patterns



Ò Creation/Notification Ò People create reminders in evenings (end of day), w/

notifications set in mornings (start of day).



Ò Creation/Notification Ò People create reminders in evenings (end of day), w/

notifications set in mornings (start of day).

Ò (not shown) Time deltas Ò Most reminders are for “short-term tasks”


2: Per task type patterns


All rem

inders

Chore (re

curri

ng)

Chore (st

andalone)

Comm. (coordinate)

Comm. (gen

eral)

Eat/Consu

me

Go (switc

h contex

t)

Go (erra

nd)

Manage acti

vity

Manage proce

ss

Del

ay (h

ours

)

72

60

48

36

24

12

0

Time deltas per task typeTime deltas per task type


Findings: per task type patterns



Ò Time deltas Ò Differ between task type.



Ò Time deltas Ò Differ between task type.

Ò (not shown) Creation/Notification Ò broadly two types of tasks:

Ò Created/set to notify during office hours Ò e.g., communicate, go somewhere

Ò Created/set to notify outside of office hours Ò e.g., manage ongoing process, chores


Patterns 3: By creation time


What is the relation between creation and notification time?




“call”

Patterns 3: By terms


“kids”




“church”



Ò On average people tend to set plans in the evening.



Ò On average people tend to set plans in the evening. Ò Most tasks that drive reminder setting are for short-term

tasks to be executed in the next 24 hours.




tasks to be executed in the next 24 hours.Ò Patterns differ between task types (suggesting the

distinctions are meaningful).




tasks to be executed in the next 24 hours.Ò Patterns differ between task types (suggesting the

distinctions are meaningful).Ò Terms and creation times are informative w.r.t.

notification time.


RQ3: Can we predict when certain tasks are most likely to happen?

Ò Motivation: Ò See if patterns are informative.

Ò Applications: Ò improve resource scheduling, Ò detect collisions Ò tailored advertising, Ò developing systems to automatically terminate

ongoing tasks/allocate time for task completion


Findings

Ò Predict notification day with ~70% accuracy. Ò Creation time provides the most information. Ò Terms provides significant additional information.


In summary

1.Studied frequent reminders, developed task type taxonomy.

2.Shown reminders’ temporal patterns

3.Demonstrated a direction in harnessing patterns; predicting notification times.


Future work

Ò User studies? Ò assumptions w.r.t. “wrapping up day, planning ahead” Ò validate/check task type taxonomy

Ò Classify task types for improved predictions? Ò More sophisticated predictive models Ò Look at additional reminder types (e.g., location-based)


Thanks!

Ò Questions?

[email protected] @dvdgrs

www.graus.co

mailto:[email protected]

http://www.graus.co

Analyzing and Predicting Task Reminders

Science

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