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  • × author_ss:"Melucci, M."
  • × year_i:[2000 TO 2010}
  1. Melucci, M.; Orio, N.: Design, implementation, and evaluation of a methodology for automatic stemmer generation (2007) 0.03 
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    Abstract
    The authors describe a statistical approach based on hidden Markov models (HMMs), for generating stemmers automatically. The proposed approach requires little effort to insert new languages in the system even if minimal linguistic knowledge is available. This is a key advantage especially for digital libraries, which are often developed for a specific institution or government because the program can manage a great amount of documents written in local languages. The evaluation described in the article shows that the stemmers implemented by means of HMMs are as effective as those based on linguistic rules.
  2. Agosti, M.; Melucci, M.: Information retrieval techniques for the automatic construction of hypertext (2000) 0.02 
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  3. Bacchin, M.; Ferro, N.; Melucci, M.: ¬A probabilistic model for stemmer generation (2005) 0.01 
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  4. Melucci, M.; Orio, N.: Combining melody processing and information retrieval techniques : methodology, evaluation, and system implementation (2004) 0.01 
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  5. Melucci, M.: Making digital libraries effective : automatic generation of links for similarity search across hyper-textbooks (2004) 0.01 
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