![](bg6.png)
after calculating the similarity between single words.
After using our name-based strategy, we obtained a
high degree of similarity between Romance
Linguistics and Latin. However, this is not the
results we want because they should have low
similarity value and should not be mapped. Second,
in the instance-based strategy, we only use word
frequencies to carry out the computation and do not
analyze the importance of words, such as, titles of
documents, key sentences in paragraphs, key words
having high weights in each sentence, etc.
Therefore, the comparison of vectors is not perfectly
precise.
6 CONCLUSION
In this paper, we proposed an ontology mapping
approach which combines two strategies. These two
strategies make use of name information and
instance information assigned to concept nodes
respectively to calculate similarities between
entities. Then an integrated approach is designed to
incorporate both strategies. The experimental results
show that ACAOM performs better than iMapper
and it improves the precision of iMapper from
+2.4% to 5.9%.
There are several aspects that can be improved in
our proposed system. (1) We could realize ontology
merging and integration in the same system.
ACAOM can be applied to other aspects of ontology
related issues, such as, queries based on distributed
ontology. (2) Our method can not support n:m
mappings at present, which are useful in many cases,
we will extend our method to deal with these cases
in the future during complex mappings.
REFERENCES
Berners-Lee, T., Fischetti,T., Francisco,M., 1999.
Weaving the web: The Original Design and Ultimate
Destiny of The World Wide Web by Its Inventor. The
publisher: Harper San Francisco USA, 1
st
edition, 240.
Buckley, C. & Lewit, A.F., 1985. Optimization of inverted
vector searches. In SIGIR’85, 8th Annual International
ACM SIGIR Conference on Research and
Development in Information Retrieval. SIGIR
Press,97-110.
Doan,anhai,2004
http://anhai.cs.uiuc.edu/archive/summary.type.html
Ehrig, M.& Sure, Y. (eds.) 2004. Ontology mapping - an
integrated approach. In ESWS’04, 1st European
Semantic Web Symposium. Proceedings of the 1st
ESWS. Lecture Notes in Computer Science., Springer-
Verlag, 76-91.
Ehrig, M. & Staab, S., 2004. QOM:Quick Ontology
Mapping. In ISWC’04, 3rd International Semantic
Web Conference. ISWC Press, 683-697.
Gruber, T.R., 1993. A translation approach to portable
ontologies. Knowledge Acquisition, 199-220.
Horrocks, 2002. DAML+OIL:a reason-able web ontology
language. Proc. EDBT. Lecture Notes in Computer
Science, Springer-Verlag, Heidelberg.
Lin, Dekang., 1998. An information-theoretic definition of
similarity. In ICML’98, 15th International Conference
on Machine Learning. ICML Press, 296-304.
McGuinness,D.L., Fikes, R., Hendler, J. & Stein, L. A.,
2002. DAML+OIL: an ontology language for the
semantic web. IEEE Intelligent Systems.
Mitra,P. & Wiederhold, G., 2002. Resolving
terminological heterogeneity in ontologies. In
ECAI’02, 15th European Conference on Artificial
Intelligence. ECAI Press.
PorterStemmer,
http://www.tartarus.org/~martin/PorterStemmer/
Resnik,P., 1995. Using information content to evaluate
semantic similarity in a taxonomy. In IJCAI’95,
International Joint Conference on Articial
Intelligence.IJCAI Press, 448-453.
Su,Xiaomeng. & Gulla, J.A., 2004. Semantic enrichment
for ontology mapping. In NLDB’04, 9th International
Conference on Application of Natural Language to
Information Systems. NLDB Press,217-228.
Tang ,J., Liang Bangyong., & Li, Juanzi., 2005, Toward
detecting strategies for ontology mapping. In
WWW’05, Workshop on Semantic Computing in the
14th International World Wide Web Conference.
WWW Press.
Vouros, G.A., Kotis,K., 2005. Extending HCONE-Merge
by approximating the intended meaning of ontology
concepts iteratively. In ESWC’05, 2nd European
Semantic Web Conference. ESWC Press, 198-210.
Wang Jianyong, Xie Zhengmao, Lei Ming, & Li
Xiaoming: Research and Evaluation of Near-replicas
of Web Pages Detection Algorithms. Chinese Journal
of Electronics.
WEBIST 2006 - WEB INTERFACES AND APPLICATIONS
386