Surety is performing system maintenance this weekend. Electronic date stamps on new Prior Art Database disclosures may be delayed.
Browse Prior Art Database

Display of the install updates dialog based on the user's behaviour patterns

IP.com Disclosure Number: IPCOM000248821D
Publication Date: 2017-Jan-13
Document File: 2 page(s) / 117K

Publishing Venue

The IP.com Prior Art Database


Most security aware users have their operating system/applications updates set to manual. This is also a default setting on many operating systems. The system updates often require a computer reboot, however the dialog to download/install these updates tends to display at inappropriate times. Times when the user is not willing to have their computer rebooted, choosing the option to delay these updates by some time period. This results in two problems, one is the annoyance of having these dialogs show up too often. Second is even worse, opening the computer to security breaches as these updates are often marked as critical, fixing security holes. This article acknowledges that many users prefer the option of the install dialog showing up, giving them power over the updates. What it is trying to solve is the dialog showing at inappropriate times, when the user is not ready to install these updates. Instead looking for times when a user would be likely to install the updates, such times being : before going to sleep or leaving for lunch.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 52% of the total text.

Display of the install updates dialog based on the user's behaviour patterns

This article is focusing on finding an appropriate time to display an “install update“ dialog for users how have manual updates turned on. An inappropriate time would be when the user is in the middle of writing a document or playing a game. While the appropriate times of showing the dialog will be just before the user leaves the computer, for example by going to lunch or for a run.

This article can be essentially simplified into two steps : Step A - The data collection that stores data from times before the user leaves their computer. Step B - Showing of the install dialog.

Step B (representing steps 1 - 4 in the above diagram) - When an “appropriate” time is identified show the user the “install update dialog” if some updates are waiting. And if the user does not allow the installation, wait for the next possible time.

Step A (representing step 0 in the diagram) - This step focuses on gathering information that indicates the user is leaving their computer. By leaving the computer we mean it being idle, asleep, or shut down. The information collection will consist of a combination of these factors :

• Time - If the user goes for lunch at 12PM on weekdays for an hour, 11:55 would be a good time to show the dialog, just before the user leaves for lunch. The same applies for the user going for a jog or going to sleep.

• Last opened application - Some people act consistently before going to sleep, for example by watching a TV show just before or playing a video game.

• Location - This information is mainly used to enhance the other data being collected. For example with time, if the user goes for lunch at 12PM when at work. If the user is at a location where they have never gone for lunch and it is 12PM (when they usually go for lunch at work) do not show an update dialog.

• Monitor user’s behaviour - This broader category includes behaviours as: the user closing browser tabs, exiting full screen mode or typing “Off to bed/lunch” in a messaging application. An example of what can be inferred is the user playing games before going the bed and leaving full screen mode (of the game), or the user closing down browser tabs before letting the computer to sleep/shut down.


This information is combined to create a statistical prediction of when the user will leave the computer for a long enough time to install the updates. The time of installing the update can be estimated from previous update install times and their size. The time period of the user leaving the computer is kept for each different session (The user going to sleep - long, the user going for a jog - shorter).

The data collected wi...