DZone
Big Data Zone
Thanks for visiting DZone today,
Edit Profile
  • Manage Email Subscriptions
  • How to Post to DZone
  • Article Submission Guidelines
Sign Out View Profile
  • Post an Article
  • Manage My Drafts
Over 2 million developers have joined DZone.
Log In / Join
  • Refcardz
  • Trend Reports
  • Webinars
  • Zones
  • |
    • Agile
    • AI
    • Big Data
    • Cloud
    • Database
    • DevOps
    • Integration
    • IoT
    • Java
    • Microservices
    • Open Source
    • Performance
    • Security
    • Web Dev
DZone > Big Data Zone > AI and Human Behavior

AI and Human Behavior

How good is artificial intelligence at predicting human behavior?

Adi Gaskell user avatar by
Adi Gaskell
·
Jan. 23, 17 · Big Data Zone · Opinion
Like (3)
Save
Tweet
4.26K Views

Join the DZone community and get the full member experience.

Join For Free

I’ve written a few times recently about the initial forays of IBM’s Watson into retail.  For instance, at the back end of last year, they launched Watson Trend to help us buy the perfect holiday gift, whilst they’ve also powered the recommendation engine at retailers such as North Face.

Both are good examples of the use of AI to help provide more accurate predictions of the things we prefer.  A good example of the work being undertaken in this area comes from a recently published paper that sees researchers develop a filtering model to do this job.

Understanding Preferences

Their method relies on the assumption that our choices are in large part determined by our membership of particular groups.  Whilst that in itself is a touch unrealistic, the tool attempts to add a degree of realism by allowing both individuals and products to belong to multiple groups at the same time.  Likewise, it doesn’t suppose that individuals may like just one item, or even items in a single group, at a particular time.

The algorithm at the heart of the model is capable of understanding, and even predicting, the resulting overlap in groups and preferences, thus rendering it, the authors claim, more accurate than current algorithms.

The authors contend that their new model is a more accurate reflection of how people typically behave, and as such as more useful for retailers. They believe it can produce behavioral patterns that are a good match for large chunks of the population, all via a model that is both quick and scalable.

AI

Published at DZone with permission of Adi Gaskell, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

Popular on DZone

  • Migrating Legacy Applications and Services to Low Code
  • Screen Sharing in Java
  • Java’s Encapsulation - When the Getter and Setter Became Your Enemy
  • A Brief History of the DMCA

Comments

Big Data Partner Resources

X

ABOUT US

  • About DZone
  • Send feedback
  • Careers
  • Sitemap

ADVERTISE

  • Advertise with DZone

CONTRIBUTE ON DZONE

  • Article Submission Guidelines
  • MVB Program
  • Become a Contributor
  • Visit the Writers' Zone

LEGAL

  • Terms of Service
  • Privacy Policy

CONTACT US

  • 600 Park Offices Drive
  • Suite 300
  • Durham, NC 27709
  • support@dzone.com
  • +1 (919) 678-0300

Let's be friends:

DZone.com is powered by 

AnswerHub logo