Context mining and integration into

Predictive Web Analytics

Julia Kiseleva (Eindhoven University of Technology),Supervised by:Mykola Pechenizkiy (Eindhoven University of Technology),

Web Predictive Analytics

What is predictive web analytics?Web predictive analytics: • aims to predict individual and aggregated characteristics indicating

visitor behavior for purposes of understanding and optimizing web usage.

• Application:o Search engines o Recommender System

• Examples:o Computational Advertisement

• Predictive web analytics tasks:o Online shop’s recommendations;o Users’ next action prediction;o Users’ intention predicting;o Personalized search result page.

Model L

Users web log

Historicaldata

labels

label?

1. training

3. application

X

y

X'

y’=L (X')

Formulations:① Classification② Regression ③ Clustering④ Scoring

labels

Testingdata

2. testing

Predictive Web Analytics

User next action prediction

Historical data. Actions ={Search, Refine Search, Click on Banner, Product view, Payment}

Search Refine Search ?Click on

BannerProduct

View

What is next?

Session 1 Search Refine Search

Click on Banner

Product View Payment

Session 3 Product View

Payment

Session 3 Search Refine Search

Refine Search

Click on Banner

Session 4 Search Refine Search

Click on Banner

Product View Payment

Session 5 Product View

Click on Banner

Search

Running Example: users’ trail predictions

Search Refine Search ?Click on

Banner Product

View

What is next?

Running Example: users’ trail predictions

Search

Refine Search

Payment

Click on Banner

Product View

1.0 2/3

1/3

1/21/4

Drop out

3/4

1/4

1

1/4

User next action prediction

ContextWhat is context? – any additional information that

Why we need context? o enhances the understanding of the instance of interest, o helps us to classify this instance or makes predictions regarding its

behavior.

• Two major context types:o Explicit – stored explicitly or given by domain expert (location, OS,

Browser) o Implicit – hidden in the data. We need techniques to discover context.

Taxonomy for explicit Context

Human Factors

Physical EnvironmentFactors

User CharacteristicsSocial EnvironmentIntent

Conditions

Infrastructure

Location

*Weather*Light*Acceleration*Audio*…

*Temperature*Humidity*…

Environment/Context

Model L

Users web log

X'

y'

Historicaldata

labels

X

y

label?

labels

Testdata

Strategies:① ?② ? ③ ?④ ?

Context-Awareness in Web Predictive

Analytics

Research QuestionsQuestion 1: How to define the context in predictive webanalytics?Question 2: How to connect context with the predictionprocess in predictive web analytics?

Context Definitio

n

Context Discover

y

Context Modelin

g

Context Mining:How define

context? Context Integratio

n

Search Refine Search ?Click on

Banner Product

View

What is next?

Running Example: users’ trail predictions

Search

Refine Search

Payment

Click on Banner

Product View

1.0 2/3

1/3

1/21/4

Drop out

3/4

1/4

1

1/4

User next action prediction

Local models

Contextual Partitioning

• Approaches to create local models:o Horizontal partitions

Users from Europe

Users from South America

Session 1 Search

Refine Search

Click on Banner

Product View

Payment

Session 3 Product View

Payment

Session 3 Search

Refine Search

Refine Search

Click on Banner

Session 4 Search

Refine Search

Click on Banner

Product View

Payment

Session 5 Product View

Click on Banner

Search

Contextual Partitioning

• Approaches to create local models:o Horizontal partitiono Vertical partition :

• Two types of behavior:o Ready to by – (Product View, Payment)o Just browsing – (Search, Refine Search, Click on

Banner) Session 1 Searc

hRefine Search

Click on Banner

Product View

Payment

Session 3 Product View

Payment

Session 3 Search

Refine Search

Refine Search

Click on Banner

Session 4 Search

Refine Search

Click on Banner

Product View

Payment

Session 5 Product View

Click on Banner

Search

Contextual Partitioning

• Approaches to create local models:o Horizontal partitiono Vertical partition :

• Two types of behavior:o Ready to by – (Product View, Payment)o Just browsing – (Search, Refine Search, Click on

Banner) Session 1 Searc

hRefine Search

Click on Banner

Product View

Payment

Session 3 Product View

Payment

Session 3 Search

Refine Search

Refine Search

Click on Banner

Session 4 Search

Refine Search

Click on Banner

Product View

Payment

Session 5 Product View

Click on Banner

Search

Context Definition

• Intuition about Context: change of user intentso User is looking for the producto User is ready to buy

Search Refine Search

Payment

Click on Banner

Product View

Intent: looking for product

Intent: ready to buy

Context Discovery

• Context definition: change of user intentso User is looking for the producto User is ready to buy

• Context discovery – apply hierarchical clustering in order to maximize prediction accuracy

Search Refine Search

Payment

Click Product

View

Intent: looking for product

Intent: ready to buy

Context-Awareness Integration

Predictive model(s)

Predictions

Training data

Context-awareness

Example: Seasonality

(winter, summer)

Example:Features set expansion

Example:Prediction adjustment

Context Integration Example

Context:User intent

DATA

Contextual Categories

Individual Learners

Mapping G

Mapping H Context

Discovery

Ready to buy

Just browsing

Context Integration Example

………………

Contextual features

DATA Environment

Contextual Categories

Individual Learners

Mapping G

Mapping H

Context Discovery

Thank you!• Context identification and

integration it into prediction models• Accurately predicting users’ desired

actions and understanding behavioral patterns of users in various web-applications

• Personalization and adaptation to diverse customer need and preferences

• Accounting for the practical needs within the considered application areas.

Summary• The main goal is to develop a generic framework

for context-aware systems for Web Predictive Analytics

• In order to archive this goal we need to answer the following questions:o How to define the context in predictive webanalytics?o How to connect context with the predictionprocess in predictive web analytics?

Questions?

Research Methodology

Implementing CAPA framework

Developing CAPA framework

Online validation (A/B testing)

Internal validation

Context-aware systems

Context definition

Context Integration Method

Application

Context-aware system

Recommendationsystems

Computational Advertisement

Information Retrieval

Normalization

Expansion

Classifier Selection

Classification Adjustment

Weighting

Domain Expert

Clustering

Contextual feature identification

History of context definition and discovery

Context YearLocation 1992Taxonomy of explicit context 1999Predictive features vs. contextual

2002

Hidden context: (clustering, mixture models)

2004

Contextual bandits 2007History of previous interaction 2008Independence of predicted class 2011Two level prediction model 2012Focus on Context Discovery 2012 -

Tim

elin

e

Research Goal • Our research aims to develop a generic

framework and corresponding techniques for introducing the contextual information in Predictive Web Analytics and accounting for the practical needs within the considered application areas.