C. Meghini, F. Sebastiani, and U. Straccia. A model of multimedia information retrieval. Journal of the ACM (JACM), 48(5):909--970, 2001. Home/Search Document Details and Download
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Fuzzy Aggregation of Palette Colors for Hybrid.. - Kushki.. (2002) (Correct)
....measurements) or queried. This paper address the latter of these issues with specic focus on the generation of database queries based on color palettes. As explained in this paper, Fuzzy Logic shows great potential as a good technique for the creation of queries composed of multiple features [4] (in this case, palette colors) Because of its vague nature, it can be further used to model human perception which is inherently imprecise and varies from individual to individual. In Section 2, the feature and sim ilarity measure employed in this system will be outlined. This will be lollowed ....
C. Meghini, F. Sebastiani, U. Straccia, "A Model of Multimedia Information Retrieval", Journal of the ACM, Vol. 48, No. 5, Sept. 2001, pp. 909-970.
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C. Meghini, F. Sebastiani, and U. Straccia. A model of multimedia information retrieval. Journal of the ACM, 48(5):909--970, 2001.
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Carlo Meghini, Fabrizio Sebastiani, and Umberto Straccia. A model of multimedia information retrieval. Journal of the ACM, 48(5):909--970, 2001.
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Carlo Meghini, Fabrizio Sebastiani, and Umberto Straccia. A model of multimedia information retrieval. Journal of the ACM, 48(5):909--970, 2001.
A System for the Fast Prototyping of Multidimensional.. - Meghini, Sebastiani.. (1999) Self-citation (Meghini Sebastiani Straccia) (Correct)
....of TIM aimed at supporting the construction of fast prototypes of MIR applications. For space reasons, the presentation just touches upon the most important aspects of ARIANNA. The readers interested in knowing more about the model or the system are referred to a long version of this paper [6]. 2. The terminological image retrieval model As any retrieval model, TIM consists of a language for representing images and queries, namely fuzzy description logic [8] and a retrieval function (implication relation) establishing the retrieval status value (RSV) of each image for each query. RSV ....
.... i to the query Q is given by the maximal degree of truth of Q(i) with respect to the knowledge base consisting of Phi(Q(d) and Sigma D , maximized over the set of content descriptions oe(i) A formal proof of the correctness and completeness of the query decomposition principle can be found in [6]. Operatively, it permits to perform query evaluation in the general context of our logic, once the subqueries involving the special symbols SPSs are identified and evaluated by the function Phi and the corresponding fuzzy assertions are collected in Phi(Q(d) Now let us see how such a Phi is ....
C. Meghini, F. Sebastiani, and U. Straccia. A model of multimedia information retrieval. Tech. Rep. B4-21-0998, CNR-IEI, Sept. 1998.
A System for the Fast Prototyping of Multidimensional.. - Carlo Meghini Fabrizio Self-citation (Meghini Sebastiani Straccia) (Correct)
....of TIM aimed at supporting the construction of fast prototypes of MIR applications. For space reasons, the presentation just touches upon the most important aspects of ARIANNA. The readers interested in knowing more about the model or the system are referred to a long version of this paper [6]. 2. The terminological image retrieval model As any retrieval model, TIM consists of a language for representing images and queries, namely fuzzy description logic [8] and a retrieval function (implication relation) establishing the retrieval status value (RSV) of each image for each query. RSV ....
.... the image i to the query Q is given by the maximal degree of truth of Q(i) with respect to the knowledge base consisting of #(Q(d) and #D , maximized over the set of content descriptions #(i) A formal proof of the correctness and completeness of the query decomposition principle can be found in [6]. Operatively, it permits to perform query evaluation in the general context of our logic, once the subqueries involving the special symbols SPSs are identified and evaluated by the function # and the corresponding fuzzy assertions are collected in #(Q(d) Now let us see how such a # is defined. ....
C. Meghini, F. Sebastiani, and U. Straccia. A model of multimedia information retrieval. Tech. Rep. B4-21-0998, CNR-IEI, Sept. 1998.
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C. Meghini, F. Sebastiani, and U. Straccia. A model of multimedia information retrieval. Journal of the ACM (JACM), 48(5):909--970, 2001.
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C. Meghini, F. Sebastiani, and U. Straccia. A model of multimedia information retrieval. Journal of the ACM, 48(5):909--970, 2001.
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C. Meghini, F. Sebastiani, and U. Straccia. A model of multimedia information retrieval. Journal of the ACM, 48(5):909--970, 2001.
Modeling Annotated Data - Blei, Jordan (2003) (14 citations) (Correct)
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C. Meghini, F. Sebastiani, and U. Straccia. A model of multimedia information retrieval. Journal of the ACM (JACM), 48(5):909--970, 2001.
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C. Meghini, F. Sebastiani and U. Straccia, "A model of multimedia information retrieval," Journal of the ACM 48(5), pp. 909-970, 2001.
Modeling Annotated Data - David Blei University (14 citations) (Correct)
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C. Meghini, F. Sebastiani, and U. Straccia. A model of multimedia information retrieval. Journal of the ACM (JACM), 48(5):909--970, 2001.
An Overview of Hybrid Possibilistic Reasoning - Liau (Correct)
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C. Meghini, F. Sebastiani, and U. Straccia. "A model of multimedia information retrieval". JACM, 48(5):909--970, 2001.
Modeling Annotated Data - Blei, Jordan (2003) (14 citations) (Correct)
No context found.
C. Meghini, F. Sebastiani, and U. Straccia. A model of multimedia information retrieval. Journal of the ACM (JACM), 48(5):909--970, 2001.
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