20180529-NOOR

Experiment design

Designer: Jérôme Euzenat (INRIA) (2017-02-16)

Revision of networks of ontologies with expansion (4 agents; 10 runs; 10000 games; delete/replace/refine/add/addjoin/refadd)

Hypotheses:

Experimental setting: Same as 20170216-NOOR replaying the same runs 20180308-NOOR (putatively) and after fixing addjoin and expansion.

Experiment

Experimenter: Jérôme Euzenat (INRIA) (2018-05-29)

Date: 2018-05-29

Lazy lavender hash: d50e70f87bca76951ec2f149dc8ae1d42b9a1a28

Classpath: lib/lazylav/ll.jar:lib/slf4j/logback-classic-1.2.3.jar:lib/slf4j/logback-core-1.2.3.jar:.

OS: stretch

Parameters: params.sh

Command line (script.sh):

#!/bin/bash

JPATH=lib/lazylav/ll.jar:lib/slf4j/logback-classic-1.2.3.jar:lib/slf4j/logback-core-1.2.3.jar:.

OPT="-DnbAgents=4 -DnbIterations=10000 -DnbRuns=10 -DreportPrecRec"

LOADOPT="-DloadDir=input/expeRun -DloadEnv -DloadAgents -DreplayGames"

for op in delete replace refine add addjoin refadd
do
   bash scripts/runexp.sh -d 4-10000-${op}-random java -Dlog.level=INFO -cp lib/lazylav/ll.jar:lib/slf4j/logback-classic-1.2.3.jar:lib/slf4j/logback-core-1.2.3.jar:. fr.inria.exmo.lazylavender.engine.Monitor ${OPT} ${LOADOPT} -DrevisionModality=${op} -DexpandAlignments=random
   bash scripts/runexp.sh -d 4-10000-${op}-protected java -Dlog.level=INFO -cp lib/lazylav/ll.jar:lib/slf4j/logback-classic-1.2.3.jar:lib/slf4j/logback-core-1.2.3.jar:. fr.inria.exmo.lazylavender.engine.Monitor ${OPT} ${LOADOPT} -DrevisionModality=${op} -DexpandAlignments=protected
   bash scripts/runexp.sh -d 4-10000-${op}-protected-nr java -Dlog.level=INFO -cp lib/lazylav/ll.jar:lib/slf4j/logback-classic-1.2.3.jar:lib/slf4j/logback-core-1.2.3.jar:. fr.inria.exmo.lazylavender.engine.Monitor ${OPT} ${LOADOPT} -DrevisionModality=${op} -DexpandAlignments=protected -DnonRedundancy
   bash scripts/runexp.sh -d 4-10000-${op}-clever java -Dlog.level=INFO -cp lib/lazylav/ll.jar:lib/slf4j/logback-classic-1.2.3.jar:lib/slf4j/logback-core-1.2.3.jar:. fr.inria.exmo.lazylavender.engine.Monitor ${OPT} ${LOADOPT} -DrevisionModality=${op} -DexpandAlignments=clever
   bash scripts/runexp.sh -d 4-10000-${op}-clever-nr java -Dlog.level=INFO -cp lib/lazylav/ll.jar:lib/slf4j/logback-classic-1.2.3.jar:lib/slf4j/logback-core-1.2.3.jar:. fr.inria.exmo.lazylavender.engine.Monitor ${OPT} ${LOADOPT} -DrevisionModality=${op} -DexpandAlignments=clever -DnonRedundancy

done

Class used: NOOEnvironment, AlignmentAdjustingAgent, AlignmentRevisionExperiment, ActionLogger, AverageLogger, Monitor

Execution environment: Debian Linux virtual machine configured with four processors and 20GB of RAM running under a Dell PowerEdge T610 with 4*Intel Xeon Quad Core 1.9GHz E5-2420 processors, under Linux ProxMox 2 (Debian). - Java 1.8.0 HotSpot

Input: Input required for reproducibility can be retrieved from: https://files.inria.fr/sakere/input/expeRun.zip Then unzip expeRun.zip -d input

Raw results

4-10000-add-clever-nr.tsv 4-10000-add-clever-nr.txt 4-10000-add-clever.tsv 4-10000-add-clever.txt 4-10000-add-protected-nr.tsv 4-10000-add-protected-nr.txt 4-10000-add-protected.tsv 4-10000-add-protected.txt 4-10000-add-random.tsv 4-10000-add-random.txt 4-10000-addjoin-clever-nr.tsv 4-10000-addjoin-clever-nr.txt 4-10000-addjoin-clever.tsv 4-10000-addjoin-clever.txt 4-10000-addjoin-protected-nr.tsv 4-10000-addjoin-protected-nr.txt 4-10000-addjoin-protected.tsv 4-10000-addjoin-protected.txt 4-10000-addjoin-random.tsv 4-10000-addjoin-random.txt 4-10000-delete-clever-nr.tsv 4-10000-delete-clever-nr.txt 4-10000-delete-clever.tsv 4-10000-delete-clever.txt 4-10000-delete-protected-nr.tsv 4-10000-delete-protected-nr.txt 4-10000-delete-protected.tsv 4-10000-delete-protected.txt 4-10000-delete-random.tsv 4-10000-delete-random.txt 4-10000-refadd-clever-nr.tsv 4-10000-refadd-clever-nr.txt 4-10000-refadd-clever.tsv 4-10000-refadd-clever.txt 4-10000-refadd-protected-nr.tsv 4-10000-refadd-protected-nr.txt 4-10000-refadd-protected.tsv 4-10000-refadd-protected.txt 4-10000-refadd-random.tsv 4-10000-refadd-random.txt 4-10000-refine-clever-nr.tsv 4-10000-refine-clever-nr.txt 4-10000-refine-clever.tsv 4-10000-refine-clever.txt 4-10000-refine-protected-nr.tsv 4-10000-refine-protected-nr.txt 4-10000-refine-protected.tsv 4-10000-refine-protected.txt 4-10000-refine-random.tsv 4-10000-refine-random.txt 4-10000-replace-clever-nr.tsv 4-10000-replace-clever-nr.txt 4-10000-replace-clever.tsv 4-10000-replace-clever.txt 4-10000-replace-protected-nr.tsv 4-10000-replace-protected-nr.txt 4-10000-replace-protected.tsv 4-10000-replace-protected.txt 4-10000-replace-random.tsv 4-10000-replace-random.txt

Result exploration

As observed in 20170216-NOOR, purely random addition leads to success rate stabilizing around 80% (non converging as seen in 20170222-NOOR):

The size of the network for random/protected tends to get very high (around 100) and the same for all operators (but for delete and addjoin):

The size for clever (and clever-nr) is lower, according to operator preservation order and growing towards that of the reference alignment:

The difference in F-measure for clever and clever with non redundancy is non oriented (this also holds for precision and recall):

Finally, clever-nr improves on recall and F-measure, but decreases precision with respect to non expansion (20180308-NOOR):

testsuccess
rate
network
size
incoherence
degree
semantic
precision
semantic
F-measure
semantic
recall
maximum
convergence
4-10000-add-clever-nr0.96590.250.700.690.693281
4-10000-add-clever0.96600.250.700.690.683709
4-10000-add-protected-nr0.791010.310.470.600.838985
4-10000-add-protected0.791010.320.460.590.828136
4-10000-add-random0.791010.320.470.600.823608
4-10000-addjoin-clever-nr0.98580.220.720.680.651856
4-10000-addjoin-clever0.98590.240.700.680.653393
4-10000-addjoin-protected-nr0.791000.340.460.590.828555
4-10000-addjoin-protected0.791010.330.460.600.838278
4-10000-addjoin-random0.791010.330.470.600.839731
4-10000-delete-clever-nr0.98150.010.980.260.152473
4-10000-delete-clever0.98130.010.980.250.141588
4-10000-delete-protected-nr0.82540.200.550.500.455010
4-10000-delete-protected0.83540.180.570.490.444031
4-10000-delete-random0.82540.200.560.490.445247
4-10000-refadd-clever-nr0.96700.230.690.730.784174
4-10000-refadd-clever0.97720.240.700.750.823708
4-10000-refadd-protected-nr0.791170.340.440.600.939985
4-10000-refadd-protected0.791190.340.450.600.909991
4-10000-refadd-random0.791180.330.440.600.9110000
4-10000-refine-clever-nr0.97380.100.870.590.443971
4-10000-refine-clever0.97400.100.850.600.472327
4-10000-refine-protected-nr0.761080.320.470.610.859978
4-10000-refine-protected0.761080.320.470.610.859967
4-10000-refine-random0.771080.330.470.600.869808
4-10000-replace-clever-nr0.97280.070.890.430.291829
4-10000-replace-clever0.97270.070.870.430.291661
4-10000-replace-protected-nr0.761010.320.470.590.807271
4-10000-replace-protected0.761010.330.470.600.837925
4-10000-replace-random0.761000.320.480.600.827939

Analysis

Analyst: Jérôme Euzenat (INRIA) (2018-08-16)

Key points:

Further experiments: none


This file can be retrieved from URL https://sake.re/20180529-NOOR

It is possible to check out the repository by cloning https://felapton.inrialpes.fr/cakes/20180529-NOOR.git

This experiment has been transferred from its initial location at https://gforge.inria.fr.

The original, unaltered associated zip file can be obtained from https://files.inria.fr/sakere/gforge/20180529-NOOR.zip