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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) 0.00 
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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.
    Type
    a
  2. Bacchin, M.; Ferro, N.; Melucci, M.: ¬A probabilistic model for stemmer generation (2005) 0.00 
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    Abstract
    In this paper we will present a language-independent probabilistic model which can automatically generate stemmers. Stemmers can improve the retrieval effectiveness of information retrieval systems, however the designing and the implementation of stemmers requires a laborious amount of effort due to the fact that documents and queries are often written or spoken in several different languages. The probabilistic model proposed in this paper aims at the development of stemmers used for several languages. The proposed model describes the mutual reinforcement relationship between stems and derivations and then provides a probabilistic interpretation. A series of experiments shows that the stemmers generated by the probabilistic model are as effective as the ones based on linguistic knowledge.
    Type
    a
  3. Melucci, M.: Making digital libraries effective : automatic generation of links for similarity search across hyper-textbooks (2004) 0.00 
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    Abstract
    Textbooks are more available in electronic format now than in the past. Because textbooks are typically large, the end user needs effective tools to rapidly access information encapsulated in textbooks stored in digital libraries. Statistical similarity-based links among hypertextbooks are a means to provide those tools. In this paper, the design and the implementation of a tool that generates networks of links within and across hypertextbooks through a completely automatic and unsupervised procedure is described. The design is based an statistical techniques. The overall methodology is presented together with the results of a case study reached through a working prototype that shows that connecting hyper-textbooks is an efficient way to provide an effective retrieval capability.
    Type
    a
  4. Agosti, M.; Melucci, M.: Information retrieval techniques for the automatic construction of hypertext (2000) 0.00 
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  5. Melucci, M.; Orio, N.: Combining melody processing and information retrieval techniques : methodology, evaluation, and system implementation (2004) 0.00 
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    Type
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