By Giuseppe Pirrò, Massimo Ruffolo, Domenico Talia (auth.), Stefano Spaccapietra (eds.)
The LNCS magazine on info Semantics is dedicated to the presentation of extraordinary paintings that, in a single means or one other, addresses learn and improvement on matters on the topic of information semantics. The scope of the magazine levels from theories helping the formal definition of semantic content material to cutting edge domain-specific functions of semantic wisdom. The magazine addresses researchers and complicated practitioners engaged on the semantic internet, interoperability, cellular details providers, facts warehousing, wisdom illustration and reasoning, conceptual database modeling, ontologies, and synthetic intelligence.
Volume XII effects from a rigorous choice between 20 complete papers acquired in accordance with a choice for contributions issued in July 2007. the quantity is a unique factor on Semantic information Warehousing.
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Additional resources for Journal on Data Semantics XII
Measuring the relative performance of schema matchers. In: Proc. of WI 2005, Compeigne, France, pp. 366–371 (2005) 6. : JHU/APL Onto-Mapology Results for OM 2006. In: Proc. of OAEI 2006, Athens, Georgia, USA (2006) 7. : Semantic coordination: a new approach and an application. , Mylopoulos, J. ) ISWC 2003. LNCS, vol. 2870, pp. 130–145. Springer, Heidelberg (2003) 8. : From Surface to Intensive Matching of Semantic web Ontologies. In: Proc. of WEBS 2004, Zaragoza, Spain, pp. 140–144 (2004) 9. : H-MATCH: an Algorithm for Dynamically Matching Ontologies in Peer-based Systems.
Table 12. 333 Results obtained by SECCO for Experiment 2 Fig. 13 shows values of Precision, Recall and F-Measure obtained by SECCO. As can be noticed, SECCO performs well. 9. 6211) for ontology 302. 5. 949 for ontology 304. Values of F-Measure that represent an overall indicator of the performance of a mapping algorithm are in all the cases high. Discussion of results and comparison with other ontology mapping algorithms In order to have an objective evaluation of SECCO, we decided to compare its average results with those of other ontology mapping approaches.
11 authors in  provide only a similarity value (related to the couple Book and Volume). For this couple, H-Match obtained the results shown in Table 7. Table 7. Comparison between SECCO and H-Match on the example of Fig. 8117 The lexical matcher correctly interprets the linguistic similarity between the Book and Volume concepts; in fact, it gives 1 as output. The high value of lexical similarity is because the Book and Volume concepts belong to the same WordNet synset and therefore are synonyms.