=Paper= {{Paper |id=None |storemode=property |title=Measuring semantic similarity within reference ontologies to improve ontology alignment |pdfUrl=https://ceur-ws.org/Vol-946/om2012_poster7.pdf |volume=Vol-946 |dblpUrl=https://dblp.org/rec/conf/semweb/CrossS12 }} ==Measuring semantic similarity within reference ontologies to improve ontology alignment== https://ceur-ws.org/Vol-946/om2012_poster7.pdf 
        Measuring Semantic Similarity within Reference
         Ontologies to Improve Ontology Alignment

                             Valerie Cross and Pramit Silwal
                   Computer Science and Software Engineering Department,
                         Miami University, Oxford, OH 45056
                                   crossv@muohio.edu




1 Mediating Matcher with Semantic Similarity

Some ontology alignment (OA) systems find an identical bridge concept in a
reference ontology to which both the source and target concept can be mapped. Then
a mapping between the two is produced. Using semantic similarity within a reference
ontology can find more mappings than with only identical bridge concepts. A wide
variety of semantic similarity measures were implemented within AgreementMaker
[1] to use semantic similarity to evaluate OA mappings [2]. Initial results of
enhancing AgreementMaker with a new matcher, the mediating matcher with
semantic similarity (MMSS) in place of its mediating matcher (MM) are in [3].
Briefly, the MMSS uses the MM to first produce a set of mappings MST between
source and target concepts with an exact match on the bridge concepts, i.e., bS = bT as

  MST = {(s, t, mapSimSR * mapSimTR) | sOS, bS , bT OR, tOT :
  (s,bS,mapSimSR,)MSR (t,bT,mapSimTR,)MTR bS=bT}

MSR contains mapping from the source O S to the reference OR using BSMlex matcher
and similarly for MTR with OT. US contains source concepts s from MSR, which are
not selected by the original MM and similarly UT for the target concepts t.
  US = {s | sOS : (s, bS, mapSimSI)MSI ∄ tOT : (s, t, simST)MST}
For each (s, t) in US x UT, semantic similarity between all their bS and bT are
calculated, and the maximum is used in determining the enhanced mapping set as

  EST ={(s, t, agg(mapSimSR, mapSimTR, bridgeSim)) | sUS, bS , bT OR, tUT :
              (s,bS,mapSimSR) MSR ( t, bT, mapSimTR,)MTR :
                bridgeSim = max bS , bT OR (semSim(bS , bT))}.

Different agg operators are possible, but here minimum is used with the rationale that
the final mapping between s and t is not any stronger than the weakest similarity
between the pairs of concepts, (s,bS), (t,bT), and (bS,bT). Different semantic similarity
measures can be used for semSim. The standard Lin semantic similarity measure is
used with information content described as in [3]. An additional threshold value may
be set to eliminate mappings in EST whose aggregated similarity falls below the
threshold. MST  EST is input to the linear weighted combination (LWC) operation
2 Experimental Results using OAEI 2011 Anatomy Track

    To compare the MMSS to the MM in OAEI 2011 AgreementMaker configuration
using its matchers and hierarchical LWCs, experiments are performed with the OAEI
2011 anatomy track and Uberon as the reference ontology. The results are shown in
Table 1. At the 0.9 threshold level, the OAEI 2011 AgreementMaker configuration
with MMSS (OAEI-MMSS) produced 2 more mappings than with MM (OAEI-MM),
but no more correct mappings. Examining the mappings showed OAEI-MMSS found
3 new correct ones but lost 3 correct ones found by OAEI-MM. Further analysis
suggests that the interaction among AgreementMaker’s matchers, its local quality
measures (LQM) used as weighting for its LWCs, and the hierarchical organization of
its LWCs have subtle effects on the mappings eventually selected for the final result.

             Table 1. OAEI 2011 AgreementMaker MM vs. its MMSS version

                                  Produced    Correct    Precision     Recall    F-measure
OAEI-MM                              1439       1348         93.7        88.9        91.2
OAEI-MMSS -0.9                       1441       1348         93.5        88.9        91.2
OAEI-MMSS-0.95                       1441       1350         93.7        89.1        91.3
OAEI-MMSS-0.95, PSM kept             1443       1353         93.8        89.2        91.4

The OAEI 2011 AgreementMaker configuration hierarchically combines its
Parametric String-based Matcher (PSM), Vector-based Multi-word Matcher (VMM)
and Lexical Similarity Matcher (LSM) represented as LWC3(LWC1(LSM+MM) +
LWC2(PSM + VMM)) using LQMs to weight each component. MMSS is substituted
for MM. Other hierarchical combinations of matchers in experiments did not perform
better than OAEI-MM. However, three different hierarchical combinations produced
new mappings not found by either the OAEI-MM or OAEI-MMSS for a total of 9
new correct mappings. More work is needed to determine possible heuristics to be
able to keep the lost 3 mappings and also retain the 9 new mappings. Examining
LQM weighting showed LQMs for MMSS are usually higher than for the PSM or
VMM; therefore, the MMSS dominates in the final results. The third table row shows
going from 0.9 to 0.95 eliminates incorrect mappings to retain the lost mappings. The
last row shows by keeping identical source-target mappings from the PSM, a higher
F-measure is achieved, better than AgreementMaker’s OAEI 2011 result.


References

1. Cruz, I. F., Stroe, C., Caimi, F., Fabiani, A., Pesquita, C., Couto, F. M., Palmonari, M.:
   Using AgreementMaker to Align Ontologies for OAEI 2011. Ontology Matching
   Workshop, International Semantic Web Conference (2011)
2. Cross, V. and Hu, X: Using Semantic Similarity in Ontology Alignment. OM Workshop,
   10th Int. Semantic Web Conference (ISWC 2011), Bonn Germany (2011)
3. Cross, V., Silwal, P., and Morell, D: Using a Reference Ontology with Semantic Similarity
   in Ontology Alignment. International Conference on Biomedical Ontologies (ICBO), July
   22 – 25, Graz, Austria (2012)