منابع مشابه
Similarity Measures over Refinement Graphs
Similarity assessment plays a key role in lazy learning methods such as knearest neighbor or case-based reasoning. In this paper we will show how refinement graphs, that were originally introduced for inductive learning, can be employed to assess and reason about similarity. We will define and analyze two similarity measures, $S_{?}$ and $S_{?}$, based on refinement graphs. The \emph{anti-unifi...
متن کاملSimilarity Measures over Refinement Graphs
Similarity assessment plays a key role in lazy learning methods such as knearest neighbor or case-based reasoning. In this paper we will show how refinement graphs, that were originally introduced for inductive learning, can be employed to assess and reason about similarity. We will define and analyze two similarity measures, $S_{?}$ and $S_{?}$, based on refinement graphs. The \emph{anti-unifi...
متن کاملSimilarity Measures in Documents Using Association Graphs
In this paper we present a new model, designated as Association Graph, to improve document representation, facilitating the ontological dimension. We explain how to generate and use this kind of graph. Also, we analyze different document similarity measures based on this representation. A classical vector space model was used to evaluate this model and measures, investigating their strengths an...
متن کاملOn Similarity Measures Based on a Refinement Lattice
Retrieval of structured cases using similarity has been studied in CBR but there has been less activity on defining similarity on description logics (DL). In this paper we present an approach that allows us to present two similarity measures for feature logics, a subfamily of DLs, based on the concept of refinement lattice. The first one is based on computing the anti-unification (AU) of two ca...
متن کاملSimilarity Reasoning over Semantic Context–graphs
Similarity is a central cognitive mechanism for humans which enables a broad range of perceptual and abstraction processes, including recognizing and categorizing objects, drawing parallelism, and predicting outcomes. It has been studied computationally through models designed to replicate human judgment. The work presented in this dissertation leverages general purpose semantic networks to der...
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ژورنال
عنوان ژورنال: Machine Learning
سال: 2011
ISSN: 0885-6125,1573-0565
DOI: 10.1007/s10994-011-5274-3