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  • × author_ss:"Melucci, M."
  • × type_ss:"a"
  1. Melucci, M.: Making digital libraries effective : automatic generation of links for similarity search across hyper-textbooks (2004) 0.02 
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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.
  2. Melucci, M.; Orio, N.: Design, implementation, and evaluation of a methodology for automatic stemmer generation (2007) 0.02 
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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.
  3. Agosti, M.; Melucci, M.: Information retrieval techniques for the automatic construction of hypertext (2000) 0.01 
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    Source
    Encyclopedia of library and information science. Vol.66, [=Suppl.29]
  4. Melucci, M.; Orio, N.: Combining melody processing and information retrieval techniques : methodology, evaluation, and system implementation (2004) 0.01 
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    Abstract
    The article describes the project an music information retrieval that has been carried out at the University of Padova, Italy. The research work has been characterized by the synergy of the modular integration of sound techniques of melody processing and of statistical information retrieval. After illustrating the background from which the project has originated, we describe the complete process, from methodology design through evaluation and system implementation. Conclusions, impacts an research in music information retrieval, and future directions are also described.

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