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Tiddler: Customised publishing based on XML profiles and XML data sources . François Paradis , C é cile Paris, Anne-Marie Vercoustre, Stephen Wan, Ross Wilkinson, MingFang Wu. CSIRO Mathematical and Information Sciences. Outline. Motivation Examples Current approaches Our approach

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Tiddler: Customised publishing based on XML profiles and XML data sources

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Tiddler customised publishing based on xml profiles and xml data sources l.jpg

Tiddler: Customised publishing based on XML profiles and XML data sources

François Paradis, Cécile Paris,

Anne-Marie Vercoustre, Stephen Wan, Ross Wilkinson, MingFang Wu

CSIRO Mathematical and Information Sciences


Outline l.jpg

Outline

  • Motivation

  • Examples

  • Current approaches

  • Our approach

  • How it works?

  • Analysis and Conclusion


Motivation why customised publishing l.jpg

Motivation: Why customised publishing?

  • Too much information: people want less information but more relevant to their need, knowledge, or task

  • On different devices at different times: paper, Web, WAP

  • (To build customer relationship)


Examples l.jpg

Examples

  • Customised Travel Guides

    • Depending on who (preferences), where to go , when to go,

    • Depending on when/where to use it

  • Corporate brochures

    • Depending on who you are and your current interest(s)


Current techniques l.jpg

Current techniques

  • Distinct versions of manually crafted documents: one for printing, one for the Web. No personalisation

    Word -> HTML; Latex -> HTML; HTML-> WAP

  • Information Retrieval: personalisation through queries, synthesis of the results; no much coherence

  • Document generation from database queries and different stylesheets: coherence but not high level semantic of the resulting document. Limited type of sources

  • Document generation using NL techniques: relies on theavailability of knowledge base in appropriate format


Tiddler approach l.jpg

Tiddler approach

  • Exploits both language generation and IR-document synthesis approaches:

    • Coherence preserved

    • Wide variety of data sources (including web pages) accessible

  • Dynamically plan documents

  • Customise information using user models

  • Generate documents for multiple media types (Paper, Palm Pilots, Web browsers, Mobile Phones)


System architecture l.jpg

Data Sources

eg. Databases,

Web

User Model

Information Need

Media Need

System Architecture

NORFOLK

Virtual Document Planner

Content Planner

Discourse

Rules

Presentation Planner

Surface Generator

Customised

Documents


User model l.jpg

User Model

  • Include

    • preferences,

    • information need,

    • Context (device)

    • historic

  • Collected via a G.U.I. Interface

  • Used to:

    • customise information to user

    • determine layout and content detail depending on media

    • encapsulate some Users’ Goal

      • Goal is about information need

      • Virtual Document Planner resolves goal using Planning techniques


Input user model l.jpg

Input: User Model

  • Name: Zoe

  • Medium: Palm Pilot

  • Destination: Melbourne

  • Date: 1 June-15 June 2001

  • Activities: Cycling, Opera, Major Mitchell

  • Travel Information:

    Accommodation (backpacker)


Xml representation l.jpg

XML Representation

<usermodel xml:space="preserve" id="Zoe">

<name>Zoe</name>

<destination> Melbourne</destination>

<date>

<start> <day>01</day> <month>June</month> <year> 2001</year> </start>

<end> <day>15</day> <month>June</month> <year>2001</year> </end>

</date>

<wants>

<activities>Cycling, Opera, Major Mitchell </activities>

<accommodation> <accom_range>Backpacker</accom_range>

</accommodation> <events/>

</wants>

<medium>palm-pilot</medium>

….

</usermodel>


Output palm pilot version l.jpg

GeneralHotelsTo DoContacts

Facts at a glance

Population: 3.3 million

Country: Australia

Time Zone: GMT/UTC plus 10 hours

Telephone Area Code: 03

Events

Major Mitchell

Output: Palm Pilot Version


Output web version l.jpg

Output: Web Version


Virtual document planner overview 1 l.jpg

Virtual Document Planner:Overview 1

The Virtual Document Planner:

  • uses Planning Techniques:

    • Goal achieved by finding subgoals that satisfy it

    • Subgoals are linked by rhetorical relations

    • Subgoals satisfied by:

      • other decomposable subgoals

      • primitive subgoals


Virtual document planner overview 2 l.jpg

Virtual Document Planner:Overview 2

The Virtual Document Planner:

  • produces a branching tree structure:

    • Node = information need goal

    • Nodes in branches = subgoals

    • Nodes linked by rhetorical relations

  • Subgoals and Goals represent:

    • content selection

    • presentation decisions


Slide15 l.jpg

Tree for

Zoe Example

Enablement

Preparation

Background

Title, Source

Joint

Further Contact

General Information

Joint

Hotels

Opera

Cycling

Major Mitchell


Virtual document planner sub stages l.jpg

Virtual Document Planner: Sub-stages

Three substages:

  • The Content Planner

  • The Presentation Planner

  • The Surface Generator


Virtual document planner sub stage 1 l.jpg

Virtual Document Planner: Sub-stage 1

The Content Planner:

  • uses Goal Planning

  • produces a tree structure

    • nodes = document content

    • Branches = rhetorical relations that may be realised with discourse markers


Virtual document planner sub stage 2 l.jpg

Virtual Document Planner: Sub-stage 2

The Presentation Planner:

  • Leaves of the tree = chosen content

  • Leaves expanded with layout mark-up of document

  • Mark-up depends on document organisation

  • Customised for particular media type.


Virtual document planner sub stage 3 l.jpg

Virtual Document Planner: Sub-stage 3

The Surface Generator:

  • Dependent on medium

  • Content and layout mark-up are mapped to:

    • text

      • XML

      • HTML

      • WML

      • Natural Language

    • graphics

      • pictures

      • tables

      • lists


Data sources l.jpg

Data Sources

  • Norfolk technology:

    • provides interface between:

      • Virtual Document Planner

      • Data sources

  • Data Sources originate from:

    • corporate data bases

    • existing web pages of known layout (wrapping)

  • Data Sources can be:

    • static: Norfolk retrieves content in advance -> XML

    • dynamic: Norfolk retrieves content as needed by Virtual Document Planner


Why are dynamic documents useful l.jpg

Why are Dynamic Documents useful?

A document can:

  • be composed using most up-to-date information

  • customise information to user

  • tailor content to particular query

  • tailored to a particular media


What are the limitations of current dynamic pages l.jpg

What are the limitations of current dynamic pages?

Dynamic pages are often:

  • statically planned with templates and stylesheets

    • Templates grow exponentially in number as document becomes more flexible

  • represented in program language code

    • makes maintenance more difficult

  • limited to filtering at document level for customisation

  • required to maintain separate templates for different media


Conclusions 1 l.jpg

Conclusions (1)

Tiddler Advantages:

  • Easier to maintain because

    • Documents use goal planning, not template based

    • Document Rules not in a program language code

  • Customisation filters and uses relevant information from parts of documents

  • Information can be gathered from multiple sources

  • Documents for different media are generated from the same document skeleton

    • Only need to update the skeleton


Conclusions 2 l.jpg

Conclusions (2)

Future Work:

- Reasoning about the discourse to provide feedback/explanations

- Dynamic and complex user model to deal with history of information delivery

- Complex user model to build customer relationship


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