Featured Articles

Analysts expect ARM to do well next year

Analysts expect ARM to do well next year

British chip designer ARM could cash in on the mobile industry's rush to transition to 64-bit operating systems and hardware.

More...
Huawei and Xiaomi outpace Lenovo, LG in smartphone market

Huawei and Xiaomi outpace Lenovo, LG in smartphone market

Samsung has lost smartphone market share, ending the quarter on a low note and Xiaomi appears to be the big winner.

More...
Intel Broadwell 15W coming to CES

Intel Broadwell 15W coming to CES

It looks like Intel will be showing off its 14nm processors, codenames Broadwell, in a couple of weeks at CES 2015.

More...
Gainward GTX 980 Phantom reviewed

Gainward GTX 980 Phantom reviewed

Today we’ll be taking a closer look at the recently introduced Gainward GTX 980 4GB with the company’s trademark Phantom cooler.

More...
Zotac ZBOX Sphere OI520 barebones vs Sphere Plus review

Zotac ZBOX Sphere OI520 barebones vs Sphere Plus review

Zotac has been in the nettop and mini-PC space for more than four years now and it has managed to carve…

More...
Frontpage Slideshow | Copyright © 2006-2010 orks, a business unit of Nuevvo Webware Ltd.
Monday, 03 February 2014 10:32

Apple wants to know your mood

Written by Nick Farrell



It can’t trust you to tell how you are feeling

It is not enough for the fruit themed cargo cult Apple to have all your data and know what ever you are doing, it now wants to know what you are feeling.

Apple has filed a patent number 20140025620 that would let your Apple gear work out what kind of mood you’re in when it comes to online purchasing. The patent is dubbed “inferring user mood based on user and group characteristic data.” According to the patent, an individual’s responsiveness to targeted content delivery can be affected by a number of factors, such as an interest in the content, other content the user is currently interacting with, the user’s current location, or even the time of day.
Jobs’ Mob reasons that a good way of improving targeted content delivery can be to infer a user’s current mood and then deliver content that is selected.

The technology analyses mood-associated characteristic data collected to produce at a baseline mood profile for a user. The user’s current mood can then be inferred by applying one or more mood rules to compare current mood-associated data to at least one baseline mood profile for the user.

According to Jobs’ Mob: “Targeted content delivery has long been an accepted means of conveying a desired message to an audience. Instead of creating a single message and delivering it to every member of the public, a content provider would prefer to identify a segment of the population that is likely to have the greatest interest in their message." One technique often used to segment a population is to identify individuals whose characteristics satisfy a target demographic for a particular item of targeted content.

However, even though an individual’s overall profile indicates that the individual is likely to be receptive to the targeted content, there are many other factors that can affect an individual’s responsiveness at a particular point in time. For example, if an individual is pre-occupied or unhappy, the individual may not be as receptive to certain types of content.

“While the development of digital content delivery has enabled new techniques for identifying user characteristics, the user characteristics are often focused on a more general understanding of an individual’s interest in targeted content. This can lead to periods of time where the targeted content delivery is misaligned, thereby resulting in decreased satisfaction for both the content provider and the content receiver.”

Nick Farrell

E-mail: This e-mail address is being protected from spambots. You need JavaScript enabled to view it
blog comments powered by Disqus

 

Facebook activity

Latest Commented Articles

Recent Comments