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Maurice Hendrix (Semi-)automatic authoring of AH.

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Presentation on theme: "Maurice Hendrix (Semi-)automatic authoring of AH."— Presentation transcript:

1 Maurice Hendrix http://prolearn.dcs.warwick.ac.uk/AH-RO-2007/ (Semi-)automatic authoring of AH

2 Outline Why automatic authoring System overview Semantic Desktop Adding resources (ranking) Future integration

3 Why automatic authoring Make authoring task easier Manual annotation is bottleneck By integrating authoring environment into semantic desktop

4 System overview

5 Concept maps and lessons are hierarchies: MOT hierarchy structure

6 Semantic Desktop Desktop where everything is stored with extra metadata We uses RDF as storage format Example RDF (also has an XML representation) :

7 Adding Resources MOT goal/domain maps are hierarchies with tree structure, siblings are concepts at the same level The Semantic Desktop can be searched for resources. They are ranked by 2 formulae Possible use of other sources like Ariadne

8 Ranking Concept oriented Article Oriented where: rank(a,c) is the rank of article a with respect to the current domain concept c; k(c) is the set of keywords belonging to the current domain concept c; k(a) is the set of keywords belonging to the current article a; |S| = the cardinality of the set S, for a given set S.

9 Selection of ranking method - snapshot

10 Equal ranks

11 Allow duplicates among siblings We call concepts in MOT at the same depth in the hierarchy Siblings The author has to make a choice. Adding to all siblings can mean students get the link multiple times Choosing one of the siblings can mean students dont always get the link when relevant.

12 Selection of duplicates/none snapshot

13 Add meta-data as separate concepts The retrieved resources might have attributes themselves If resources have further attributes, these can be added as domain attributes in MOT The resource can also be made into a domain concept with its own separate domain attributes

14 Add metadata as attributes

15 Add metadata as Separate concepts

16 Separate concepts/ attributes snapshot

17 Compute resource keywords as set The number of times a keyword occurs might indicate the relevance of the keyword. The ranking formulae can be computed on sets of keywords or multisets.

18 Set/ multiset snapshot

19 Before MOT hierarchy snapshot

20 After MOT hierarchy snapshot

21 Future integration noticed steep learning curve and confusion Integrating Enricher into MOT could help Currently creating WebEnricher

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28 Questions?


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