@techreport{TR-IC-19-01,
   number = {IC-19-01},
   author  = {Gabriel Oliveira dos Santos \and Juliana Medeiros Destro
                   \and Julio Cesar dos Reis},
   title   =   {Investigating  neighbour  concepts  for  cross-lingual 
                   ontology alignment},
   month = {February},
   year = {2019},
   institution = {Institute of Computing, University of Campinas},
   note = {In English, 23 pages,
    \par\selectlanguage{english}\textbf{Resumo}
       Cross-lingual  ontology  alignments  play  a  key  role for the
       semantic  integration of data described in different languages.
       The  task of automatic cross-lingual ontology matching requires
       exploring  similarities  measures.  Such  measures  compute the
       degree  of  relatedness between two given terms from ontology's
       concepts.  Although  the  literature  has  extensively  studied 
       similarity  measures  for  monolingual ontology alignments, the
       use  of  similarity  measures for the creation of cross-lingual
       ontology  mappings  still  requires  further  research. In this
       work,  we  define  an  algorithm  for  automatic  cross-lingual 
       ontology  matching  based on the analysis of neighbour concepts
       to   improve  the  effectiveness  of  the  composed  similarity 
       approach,  a  technique  to  calculate the degree of similarity
       between  concept  contents in different languages. Experimental
       results  with  OAEI  datasets  indicate that our novel approach
       including  neighbour  concepts for mapping identification has a
       good effectiveness.
  }
}