Difference between revisions of "NSByGrounding"
DavidCarral (Talk | contribs) (→Code and Tutorial) |
DavidCarral (Talk | contribs) (→Code and Tutorial) |
||
| Line 321: | Line 321: | ||
Frame example containing one axiom with one nominal schema and two appearances: | Frame example containing one axiom with one nominal schema and two appearances: | ||
| − | |||
[ | [ | ||
Revision as of 20:42, 14 June 2011
Nominal Schema Reasoning by Grounding
This page contains the implementations of nominal schema reasoning using naive and smart grounding.
Contents
[hide]Introduction
In this page we include the empirical evaluation of several ontologies selected from the TONES repository (reference?). For each experiment one or more axioms containing nominal schemas were added to each ontology. Occurences of nominal schemas are grounded with all possible combinations of individuals contained in the knowledge bases. After the grounding reasoning times (using Pellet after grounding) are averaged over 100 runs, and load time is reported separately. We are particularly interested in finding what are the limits of lhis implementation varying both the number of different nominal schemas and their number of occurrences per axiom.
Testing was performed using a 64-bit Windows 7 computer with an Intel(R) Core(TM) i5 CPU processor. A java JDK 1.5 version, allocating 3GB as the minimun for the java heap and 3.5GB as the maximun, was used for each experiment.
Naive Implementation
Although not very time-efficient this implementation will serve as a baseline for development and testing of more optimised algorithms, and also shows that even the grounding approach can be used for small use cases or for initial testing.
The section includes testing data obtained from different experimets showing the feasibility of this implementation when the number of different nominal schemas per axiom is low.
Java code to ground axioms containing nominal schemas to a given ontology is also included. After the grounding reasoning tasks can be performed with the ontology using any reasoner available just as usual(the java program was built for testing purposes only and therefore it is not an optimised generic algorithm).
Ontologies
We present in this section the metrics of the ontologies used for the Naive implementation
| Ontology | Classes | Annotation P. | Data P. | Object P. | Individuals |
| Fam | 4 | 0 | 1 | 11 | 5 |
| Swe | 189 | 1 | 6 | 25 | 22 |
| Bui | 686 | 15 | 0 | 24 | 42 |
| Wor | 1842 | 6 | 0 | 31 | 80 |
| Tra | 445 | 2 | 4 | 89 | 183 |
| FTr | 22 | 2 | 6 | 52 | 368 |
| Eco | 339 | 2 | 8 | 45 | 482 |
Testing results
This section contains two tables showing the reasoning time results for the ontologies when axioms with different combinations of nominal schemas are added.
Adding one axiom to each Ontology
For every experiment only one axiom was added to each ontology varying the number of different nominal schemas and their number of appearances.
| Ontology | Plain | 1 different ns | 2 different ns | 3 different ns | ||||||||
| Name | Ontology | 2 app | 8 app | 2 app | 4 app | 2 app | ||||||
| Fam (5) | 0.01 | 0.00 | 0.01 | 0.00 | 0.01 | 0.01 | 0.01 | 0.00 | 0.01 | 0.00 | 0.04 | 0.02 |
| Swe (22) | 3.58 | 0.08 | 3.73 | 0.07 | 3.73 | 0.11 | 3.85 | 0.10 | 3.88 | 0.11 | 10.86 | 1.11 |
| Bui (42) | 2.7 | 0.16 | 2.5 | 0.15 | 2.47 | 0.15 | 2.75 | 0.26 | 3.05 | 0.36 | 1'14 | 6.68 |
| Wor (42) | 0.11 | 0.04 | 0.12 | 0.05 | 1.48 | 0.87 | 1.1 | 0.55 | 1.88 | 1.03 | 197'12 | 5'15 |
| Tra (183) | 0.05 | 0.03 | 0.05 | 0.02 | 0.05 | 0.02 | 5.76 | 1.76 | 9.9 | 3.73 | OOM | OOM |
| FTr (368) | 0.03 | 4.28 | 0.05 | 5.32 | 0.09 | 5.51 | 35.53 | 42.73 | 1'18 | 9'30 | OOM | OOM |
| FTr (368) | 0.04 | 0.24 | 0.07 | 0.02 | 0.10 | 0.04 | 56.59 | 13.67 | 53.32 | 35.35 | OOM | OOM |
Adding several axioms to each Ontology
For every experiment several axioms was added to each ontology including 1 or 2 different nominal schemas each.
| Name | No axioms added | 20 axioms, 1 ns | 10 axioms, 2 ns | |||
| Fam (5) | 0.01 | 0.00 | 0.01 | 0.00 | 0.02 | 0.01 |
| Swe (22) | 3.58 | 0.08 | 3.42 | 0.08 | 3.73 | 0.28 |
| Bui (42) | 2.7 | 0.16 | 2.69 | 0.25 | 5.7 | 3.21 |
| Wor (80) | 0.11 | 0.04 | 0.23 | 0.28 | 12.42 | 6.88 |
| Tra (183) | 0.05 | 0.03 | 0.32 | 0.15 | 1' 43.54' | 43.63 |
| FTr (368) | 0.03 | 4.28 | 0.52 | 11.33 | OOM | OOM |
| FTr (368) | 0.04 | 0.24 | 0.65 | 0.3 | OOM | OOM |
Code and Tutorial
This section presents java code to ground axioms with nominal schema for a given ontology. OWL API library needs to be added to the classpath for this task.
First the user needs to write down the frame with the axiom we want to ground to the knowledge base and store in a .owl file. It can be written with any text editor will do modifying the text extension from ".txt" to ".owl". This file should be placed in the same folder as our ontology.
Frame example containing one axiom with one nominal schema and two appearances:
[
- rdf:type owl:Class;
- rdfs:subClassOf :frameClass1;
- owl:intersectionOf(
- [ rdf:type owl:Restriction;
- owl:onProperty :property1;
- owl:someValuesFrom [ rdf:type owl:ObjectVariable; owl:variableId ”v1” ]
- ]
- [ rdf:type owl:Restriction;
- owl:onProperty :property2;
- owl:someValuesFrom
- [ rdf:type owl:ObjectVariable;
- owl:variableId ”v1” ]
- )
].
The blank node [ rdf:type owl:ObjectVariable; owl:variableId "v1"]
The program will start and prompt the user for the path for both the ontology and the frame and for the names of these. After execution a new file with appear with the same name as the ontology followed with the word "Grounded.owl". The new file contains all axioms in the previous ontology and all the all possible grounded combinations of individuals for the defined frame.
The program is only available for Turtle Syntax. A converter of OWL syntax is available in: [1]
