ARTICLE{emaf13,
  author = {L. Eld\'en and M. Merkel and L. Ahrenberg and M. Fagerlund},
  title = {Computing Semantic Clusters by Semantic Mirroring and Spectral Graph
	Partitioning},
  journal = {Mathematics in Computer Science},
  year = {2013},
  volume = {7},
  pages = {293-313},
  doi = {10.1007/s11786-013-0159-4},
  abstract = {Using the technique of semantic mirroring a graph is
                  obtained that represents words and their
                  translations from a parallel corpus or a bilingual
                  lexicon.  The connectedness of the graph holds
                  information about the semantic relations of words
                  that occur in the translations. Spectral graph
                  theory is used to partition the graph, which leads
                  to a grouping of the words in different clusters. We
                  illustrate the method using a small sample of seed
                  words from a lexicon of Swedish and English
                  adjectives and discuss its application to
                  computational lexical semantics and lexicography.},
  keywords = {semantics, cluster, bilingual, dictionary, mirroring,
                  WordNet, graph, spectral, partitioning, adjacency,
                  graph Laplacian, Fiedler vector, matrix,
                  eigenvector, eigenvalue},
  owner = {laeld},
  timestamp = {2013.09.09}
}