Writing for Machines & Humans User Context and Prediction - - PowerPoint PPT Presentation

Writing for Machines & Humans

User Context and Prediction

Information in cohabitation with IoT, Chatbots, and AI

• molecular
• dynamic
• ubiquitous
• spontaneous
• ffered
• profiled

information4zero.org

Overview

○ Define user context ○ Examples of user context ○ How to derive user context ○ Current research into prediction methods ○ How prediction may be used to drive future technologies

What’s your context?

What is user context?

Any information that is relevant in defining the situation of a user (or device)

Context is not static.

It’s an observation of a particular time space.

Context in AI-related technology

• Context is a matrix of detectable properties.
• It is volatile and adaptive.
• Often triggered (sensors, devices, location…).
• It probably has consequences that can be predictable.

The goal of user context...

...is to detect users’ needs and possibly make the content personal.

Why is user context important?

• Allows us to deliver information that is relevant to a specific user

at a specific time and place

• Improves the quality of the interaction
• Provides a rich user experience

Elements of user context

• dynamic - total context is in a constant state of change, although there

may be fixed states (i.e. birthdate, gender)

• matrix - incorporates multi-states

■ Identity ■ Time ■ Location ■ Activity

Context Classification

Context Classification

• Device state
• User state

Computer screen Smart phone Smart watch Home alarm monitor 6 user context classifications*

*Stephan Sigg, TU Braunschweig Institute of Operating Systems and Computer Networks www.ibr.cs.tu-bs.de

Identity

• Profile
• Role
• Access rights
• Level of expertise
• Social status
• Organizational status

Time

Location

Activity

• Moving
• Programming
• Documenting

Constitution

Biological

• Heart rate
• Blood sugar

Mood

• Angry
• Frustrated
• Zen

Environment

Physical

• Lighting
• Temperature
• Noise level
• Acceleration

Technological

• Network
• Wifi

Equipment

• Glasses
• Smart watch
• Smart phone
• Keyboard

How can we know a user’s context?

Deriving context states (user and device)

• Authentication data
• User profile
• Sensors
• Social analysis

Deriving user context via authentication

name gender job title user role user experience city & country of residence company

Deriving user context via authentication

Hi toni. Welcome back Hi toni. How’s the weather in [city]? Hi toni. Would you like to start writing? Hi toni. Would you like to manage a project? name city & country of residence user role

Deriving user context via sensors

device preference geolocation ambient light temperature motion headphone use time nearby places

Sensors

Industry Sensors provide context of machines and automation.

Sensors

‘Us’ Sensors provide context of people.

‘Dig deep into your shoppers' behavior. Analyze foot traffic patterns, visualize conversion rate, calculate frequency of returning visitors, and build a complete shopper profile.’ countbox.us

Deriving user context via social media

content hashtags sentiments preferences bias

Social Sensing

‘During events raising social alarm, such as earthquakes, contents shared by users of social media, if properly analyzed, allow you to have a real-time picture of the evolving situtation, the areas involved and the consequences. Users act as social sensors and their contents are valuable sources

• f information for emergency

managers.’ socialsensing.it

Group Context

When it’s not possible to derive individual context, use group context.

Context prediction

The Future of Context

Sensors and algorithms

What is context prediction?

The prediction of future context based on historical context states and extrapolation of future context states. Current research models: infer present context and predict future context

How can we predict user context?

1. Build a history of user context states 2. Classify context states 3. Learn behaviors based on context states 4. Use algorithms to extrapolate likely future states Ex: predicting location based on past behavior

User Context Prediction Model

Low level High level Individual

Recap

• Context is any information that is relevant

in defining the situation of a user (or device).

• A context state an observation of a

particular time space.

• Context states are dynamic.
• Context allows us to deliver information

that is relevant to a specific user at a specific time and place.

• Classification of context states:

○ Identity ○ Time ○ Location ○ Activity ○ Constitution ○ Environment

• Context can be sensed and inferred.
• In the future we’ll use models that predict

user behavior and provide context.

Follow me on Linkedin:

www.linkedin.com/in/toniressaire/

email:

toni.ressaire@info4design.com

Writing for Machines & Humans

A new information delivery model for modern contexts. 18-hour online course Who writes content for voice interfaces such as Alexa and Google Assistant? It could be you. firehead.net/training

training: