1. Ontology Partition for Browsing
Qingxia Liu

2. Content
An Example
Background
Related Work
Our Method

3. BackGround Ontology Goal
describes the types of things that exist (classes), the relationships between them (properties) and the logical ways those classes and properties can be used together (axioms).1
Goal
Give a good representation of contents of an ontology document by clustering and ordering 1.

4. An Example
FOAF ( ) : 13 classes, 62 properties, 1 ontology (76 terms) + 13 other

5. Users’ Motivations ( When Browsing an Ontology )
Understanding/Learning
For Use
e.g. using a concept to annotate some instances
Modularization
For Reuse
e.g. add some concepts to a new ontology under developing
Error Checking
For Developing
e.g. checking whether relations of concepts are semantically correct in the ontology under developing
Comparing
For Matching
e.g. matching concepts in two ontologies manually by browsing the concept and their related concepts

6. Specification Page

7. Program Ontology（http://www.bbc.co.uk/ontologies/po）
BBC Program Ontology（

8. Related Work Ontology Browsing Ontology Partition
LODE, Parrot, Protege
Ontology Partition
logic-based method
(MO’09) Extracting Modules from Ontologies: A Logic-based Approach
structure-based method
(ISWC’04)Structure-Based Partitioning of Large Concept Hierarchies
bisection
(ISWC’06)Block Matching for Ontologies. 

9. LODE (with reasoning)

10. Partitioning: [ISWC 2004]
Structure-Based Partitioning of Large Class Hierarchies
structure-based
w(<i,j>) = [num(eij)+num(eji)] / d(i)
island
connected
any w(e-MST)>w(external edges)
size
iterative
height: min(w(e-MST))
关联的边数占起点总度数之比

11. Partitioning: [ISWC 2006] Block Matching for Ontologies VDoc + VSM
VDoc: local description + neighboring info
hierarchical bisection

12. Our Method Clustering Topological-based Ordering literal similarity
value of attributes (data properties)
dependency similarity
relationship (object properties) to the same subject
structural closeness
Topological-based Ordering

13. References
Peroni, S., Shotton, D., & Vitali, F. (2012). The Live OWL Documentation Environment: a tool for the automatic generation of ontology documentation. In Knowledge Engineering and Knowledge Management (pp ). Springer Berlin Heidelberg.
Peroni, S., Shotton, D., & Vitali, F. (2013). Tools for the automatic generation of ontology documentation: a task-based evaluation. International Journal on Semantic Web and Information Systems (IJSWIS), 9(1),
Grau, B. C., Horrocks, I., Kazakov, Y., & Sattler, U. (2009). Extracting modules from ontologies: A logic-based approach. In Modular Ontologies(pp ). Springer Berlin Heidelberg.
Stuckenschmidt, H., & Klein, M. (2004). Structure-based partitioning of large concept hierarchies. In The Semantic Web–ISWC 2004 (pp ). Springer Berlin Heidelberg.
Hu, W., & Qu, Y. (2006). Block matching for ontologies. In The Semantic Web-ISWC 2006 (pp ). Springer Berlin Heidelberg.
Fjällström, P. O. (1998). Algorithms for graph partitioning: A survey.Linköping electronic articles in computer and information science, 3(10).
Andersen, R., Chung, F., & Lang, K. (2007). Local partitioning for directed graphs using PageRank. In Algorithms and Models for the Web-Graph (pp ). Springer Berlin Heidelberg.
Frick, M., van Aardt, S., Dlamini, G., Dunbar, J., & Oellermann, O. (2005). The directed path partition conjecture. Discussiones Mathematicae Graph Theory, 25(3), 331.

14. Thank you~

15. Browsing Live OWL Document Environment
automatically generate HTML documentation for OWL or OWL2 ontologies
extracts classes, props, indivisuals, meta-modeling, general axioms, SWRL rules, namespaces declarations
Manchester Syntax

16. Our Method Block Term dependency graph
a set of RDF sentences that describe the same subject
Term dependency graph
V: the set of terms (class, property)
if s2 appears in the block of s1, then <s1,s2>∈E

17. Graph Partitioning undirected graph directed graph local optimization
distance-based: Fiedler vector
multi-level method
directed graph
PageRank based[IM’08]
local partitioning, with given seed
kernel based[DMGT’05]
path partition, (1,λ-1)partition
kernel: an independent set;
λ-partitionable: (a,b)-partition, a+b=λ(D)(the order of the longest path)
no odd cycles, acyclic, unicyclic

18. Functions helps Understanding
Sorting
Clustering / Partitioning
Reasoning
Verbose (to NL)
e.g. Manchester Syntax
Filtering / Searching / Querying