© 2001 empolis uk1 topic maps, newsml and xml: possible integration and implementations. by soelwin...
TRANSCRIPT
© 2001 empolis UK 1
Topic Maps, NewsML and XML:Possible Integration and
Implementations.
By Soelwin Oo.
© 2001 empolis UK 2
Introduction
Integration of Topic Map Technologies
K42 & NewsML
Implementation of Topic Map Technologies
Pitfalls of Topic Map Ontology Merging
© 2001 empolis UK 3
Topic Maps
Capture concepts
Impose Knowledge on to Data
Create Knowledge Based Relationships
Powerful Knowledge & Resource Retrieval
© 2001 empolis UK 4
NewsML
Developed by the IPTC
XML Based
Possess Topic Ontology Metadata
Content Driven Approach For Topic Map Navigation
© 2001 empolis UK 5
NewsML & Topic Map Integration
Example IPTC Topic Set
<TopicSet Duid="iptc.importance" FormalName="Importance"> <Comment xml:lang="en">Relative significance of the metadata applied to a NewsComponent.</Comment> <Topic Duid="imp1"> <TopicType Scheme="IptcTopicType" FormalName="Importance"/> <FormalName Scheme="IptcImportance">High</FormalName> <Description xml:lang="en">The metadata is very important.</Description> </Topic> <Topic Duid="imp2"> <TopicType Scheme="IptcTopicType" FormalName="Importance"/> <FormalName Scheme="IptcImportance">Medium</FormalName> <Description xml:lang="en">The metadata is quite important.</Description> </Topic> <Topic Duid="imp3"> <TopicType Scheme="IptcTopicType" FormalName="Importance"/> <FormalName Scheme="IptcImportance">Low</FormalName> <Description xml:lang="en">The metadata is of low importance.</Description> </Topic></TopicSet>
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NewsML & Topic Map Integration Topic Properties:
– Formal Name– Description– Topic Type
NewsML Topic ‘High’:
<Topic Duid="imp1"> <TopicType Scheme="IptcTopicType" FormalName="Importance"/> <FormalName Scheme="IptcImportance">High</FormalName> <Description xml:lang="en">The metadata is very important.</Description> </Topic>
© 2001 empolis UK 7
FormalName
XTM representation:
NewsML & Topic Map Integration
<FormalName Scheme="IptcImportance">High</FormalName>
<topicMap> <topic id="t-IptcImportance "> <instanceOf> <subjectIndicatorRef xlink:href="http://www.TopicMaps.org/xtm/1.0/index.html#topic" /> </instanceOf> <baseName> <baseNameString>IptcImportance</baseNameString> </baseName> </topic>
<topic id="t-High"> <instanceOf> <subjectIndicatorRef xlink:href="http://www.TopicMaps.org/xtm/1.0/index.html#topic" /> </instanceOf> <baseName> <scope> <topicRef xlink:href="#t-IptcImportance " /> </scope> <baseNameString>High</baseNameString> </baseName> </topic></topicMap>
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NewsML & Topic Map Integration Description
XTM representation:
<Description xml:lang="en">The metadata is very important.</Description>
<topicMap> <topic id="t-High">
<baseName> <scope> <topicRef xlink:href="#t-IptcImportance " /> </scope> <baseNameString>High</baseNameString> </baseName>
<baseName> <scope> <topicRef xlink:href="#t-Description " /> </scope> <scope> <topicRef xlink:href="#t-xml:lang=en " /> </scope> <baseNameString> The metadata is very important.</baseNameString> </baseName>
</topic></topicMap>
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TopicType
XTM representation:
<TopicType Scheme="IptcTopicType" FormalName="Importance"/>
<topicMap> <topic id="t-High"> <instanceOf> <topicRef xlink:href="#t-Importance" /> </instanceOf>
<baseName> <scope> <topicRef xlink:href="#t-IptcImportance " /> </scope> <baseNameString>High</baseNameString> </baseName>
<baseName> <scope> <topicRef xlink:href="#t-Description " /> </scope> <scope> <topicRef xlink:href="#t-xml:lang=en " /> </scope> <baseNameString> The metadata is very important.</baseNameString> </baseName> </topic>
</topicMap>
NewsML & Topic Map Integration
© 2001 empolis UK 10
NewsML & Topic Map Integration Instance/Type Relationships of ‘Importance’
Topic SetTopicBaseName:”Importance”Scope:”IptcTopicType”
TopicBaseName:”High”Scope:” IptcImportance”
TopicBaseName:”Medium”Scope:” IptcImportance”
TopicBaseName:”Low”Scope:” IptcImportance”
Instance
Instance
Instance
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NewsML Topic Map Implementation
Currently only possess TopicType/Instance relationships
Topics can possess Occurrences to ‘Addressable Resources’
Relate NewsML articles as Occurrences of Ontology Topics
Implement Resource Retrieval Mechanism
© 2001 empolis UK 12
NewsML Topic Map Implementation Methodology for TopicType/Instance driven
Resource Retrieval1. Obtain a NewsML document that is located in a uniquely
addressable location.(For example an URL)
2. Create this document as an Occurrence of all the Ontology Topics that occur within it.
3. From this document, list all the Topics that have this document as an Occurrence.
4. The user can then choose a particular Topic of interest from the list and select to retrieve other addressable Occurrences of
that Topic.
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NewsML Topic Map Implementation
Content Driven Approach to Topic Map Navigation
User’s starting point is the Base Ontologies instantiated within NewsML article
Presentation of sets of related Topics
Retrieval of sets of related Resources
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NewsML Topic Map Implementation
Topic Association Driven Resource Retrieval
Topic Association Powered Occurrence ‘Filtering’
Resource Channel creation
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Create Topic Association Template ‘Channel’ Members:
Arcs:
Role >> Ontology Topic to be played by Topic Type >> Ontology Topic
Role >> Channel Topic to be played by Topic Type >> Channel Topic
NewsML Topic Map Implementation
from Channel Topic to Ontology Topic: includes the topic of
For example:Sport Channel <includes the topic of> Football
from Ontology Topic to Channel Topic: is assigned to
For example:Football <is assigned to> Sport Channel
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NewsML Topic Map Implementation Instantiate ‘Channel’ Topic Association Template
For Example:
Associated with ‘Sport Channel’:FootballBasket BallCricketSporting CompetitionEtc…
Associated with ‘Business Channel’:NasdaqCompanyFT IndexEtc…
Associated with ‘John’s Channel’:NasdaqFootballKnittingEtc…
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NewsML Topic Map Implementation
Process incoming NewsML documents
Create documents as Occurrences of Ontology Topics
Segregate Documents according to Ontology Topic Channel association
Display Channelled Documents
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NewsML Topic Map Implementation
Football
FT Index
Knitting
Cricket
Nasdaq
NewsML News Feed
NewsMLProcessor
Sport Channel
Business Channel
John's Channel
Football
Cricket
Nasdaq
FT Index
Nasdaq
Football
Knitting
Process news feed
Filter documents according to
associated Channel Topic
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NewsML Topic Map Implementation Create the individual documents as Occurrences
of their respective Ontology Topics.
Segregate the Occurrences of the Ontology Topics according to their associated Channel Topics.
Sports Channel
Football
Cricket
Channel Topic Ontology Topics NewsML Resources
Football
Cricket
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Integration of Multiple Topic Maps Existence of additional Custom Vocabularies Potential for duplication of Topics
Water/H2O
H2
H2OWater
IceSteam O2
consists of consists of
IceSteam O2 H2
can exist as
can exist as consists of
consists of
Topic
Association
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Integration of Multiple Topic Maps
Ontology Merging provides a richer network of Knowledge
Solutions for duplicate Topic identification– Unique Topic ID– Unique basename-scope pairs– Name/ID Mapping Tables– Common Reference Ontology
No panacea for Ontology Merging
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Conclusion
Steps for XML Ontology capturing
Simple TopicType/Instance based Resource Retrieval
Topic Association driven Occurrence Filtering
Topic Map Ontology Merging