personalization and web design monica bonett, ukoln, university of bath, uk m.bonett@ukoln.ac.uk

Personalization and Web Design

Monica Bonett, UKOLN, University of Bath, UK

M.Bonett@ukoln.ac.uk

Overview

• Motivation for providing personalization

• Terms and Techniques

• Issues: Privacy, Usability

• Use of Frameworks and Standards

• Examples in Learning and Teaching

• The IMesh Toolkit Project

Why Tailor Content?

• Build personal relationships– treat the user as an individual– increase user loyalty

• Control information overload

• Improve accessibility– cater for variation in physical capabilities– adapt to different devices or connection modes

Desired Outcomes

• Increase user satisfaction

• Repeat visits– e.g. saved information

• Increase sales or popularity

…. in general, to meet the user’s needs or preferences

Kinds of Preferences

• Look and feel

• Channels of information

• Customise parameters e.g. search

• Methods of delivery

• Tastes/interests (recommendations)

How preferences are stated

• Explicitly– Form filling– Ratings

• Inferred– click-throughs– purchases– can be implicit

Using the Preferences of Others

• Commonly used for recommendations

• Collaborative Filtering– recommendation seeker expresses preference by

rating an item/s– matching people determined by comparing tastes– recommendation/s generated

• Various algorithms

Issues: Usability

• Personalization is not an excuse for poor usability

• Cater for users who want to do sophisticated customisation, and those who will do none

• Provide adequate defaults to meet basic needs• Monitor usage patterns

Issues: Privacy

• Potentially large amounts of information are collected, sometimes implicitly

• P3P: a W3C proposal

• Privacy Statements– exactly what information is collected– how it is used (why is it needed ?)– how widely shared

Standards and Frameworks

The Argus Framework

Users ContentUser Interface Layer

Personalization

Profile Layer

Specific ValuesUser Profile

Personalization rules

Personalization rules

ContentProfile

Vocabulary Layer

Set of Attributes Content Attributes

User Attributes

Framework Components

• Users have profiles that represent their interests and behaviours

• Content is profiled, based on a set of attributes that are assigned specific values

• The business context has certain rules that govern how personalization happens. – match attributes of the content with attributes

captured in the user profile to determine which content to display.

Describing Users: Metadata

• IMS– describes characteristics of a learner to enable

exchange of learner information– structured information model (XML binding)

• eduPerson– EDUCAUSE/Internet2 task force– LDAP (directory building)

Example 1: IMS

• example attributes – identification (names, addresses, demographics)– accessibility (cognitive, technical, physical,

language)– interest (information describing hobbies and

recreational activities)

Example 2: eduPerson

• Example attributes– eduPersonAffiliation (person’s relationship to

the institution student, staff etc.)– eduPersonNickname (informal name)– preferredLanguage

Accessing profiles: SOAP

• W3C working draft (Version 1.2)

• Supports communication in a distributed environment

• Exchange of structured information based on XML

• User preferences could be exchanged in this way

SOAP Example

• Get price of books from ISBN number#!/usr/bin/perl use SOAP::Lite;

$s = SOAP::Lite -> uri('urn:xmethods-BNPriceCheck') -> proxy('http://services.xmethods.net/soap/servlet/rpcrouter');

my $isbn = '0201704471';

print $s->getPrice(SOAP::Data->type(string =>$isbn))->result;

Contact SOAP server

Contact SOAP server

Data: ISBNData: ISBN

Send data and get result

Send data and get result

The IMesh Toolkit

Gateway service(s)Gateway service(s)

Gateway service(s)Gateway service(s)

Profiledatabase

Authdatabase

AccessProfile AccessAuth

Register UpdateProfile

CGI/HTTP

Athens

SOAP

ODBC

Portability: the vision

"For the end user it would be a much better world if he or she could simply have a program pass a collection of history and opinion data to each system he or she wishes to interact with and instantly obtain personalized behaviour and where appropriate recommendations from it” (Cliff Lynch, June 2001)

Sharing User Descriptions

• Example: P3P - a W3C proposed recommendation– users can describe their privacy preferences– websites disclose how they handle information– make information available in machine-readable

format

• Identify commonality

• Allow for variation

Acknowledgments

The IMesh Toolkit Project

• Funded by JISC/NSF

• Based at UKOLN

• Working with Pete Cliff, Rachel Heery, Andy Powell and Richard Waller, ILRT (Bristol), ISP (University of Wisconsin, USA)

• In collaboration with Resource Discovery Network (RDN) and Subject Portals Project (SPP)

• Thanks also to Keith Instone and Argus Associates