An attractive property of attribute-value grammars is their reversibility. Attribute-value grammars are usually coupled with separate statistical components for parse selection and fluency ranking. We propose reversible stochastic attribute-value grammars, in which a single statistical model is employed both for parse selection and fluency ranking.

Mining design patterns from source code is significant for improving the intelligibility and maintainability of software. In this paper, we present a new design pattern matching method based on fuzzy, in which matrix model is used for describing both design pattern and source code, and design pattern’s static and dynamic information is defined as fuzzy attribute value for measuring the matching...

Probabilistic analogues of regular and context-free grammars are wellknown in computational linguistics, and currently the subject of intensive research. To date, however, no satisfactory probabilistic analogue of attribute-value grammars has been proposed: previous attempts have failed to define a correct parameter-estimation algorithm. In the present paper, I define stochastic attribute-value...

Dynamic language library developers face a challenging problem: ensuring that their libraries will behave correctly for a wide variety of client programs without having access to those client programs. This problem stems from the common use of two defining features for dynamic languages: callbacks into client code and complex manipulation of attribute names within objects. To remedy this proble...

Attribute grammars are a powerful specification paradigm for many language processing tasks, particularly semantic analysis of programming languages. Recent attribute grammar systems use dynamic scheduling algorithms to evaluate attributes on demand. In this paper, we show how to remove the need for a generator, by embedding a dynamic approach in a modern, object-oriented and functional program...

Although Attribute Grammars were introduced long ago, their lack of expressive-ness has resulted in limited use outside the domain of static language processing. With the new notion of Dynamic Attribute Grammars deened on top of Grammar Couples, informally presented in a previous paper, we show that it is possible to extend this expressiveness and to describe computations on structures that are...

Since big data sets are structurally complex, high-dimensional, and their attributes exhibit some redundant irrelevant information, the selection, evaluation, combination of those large-scale pose huge challenges to traditional methods. Fuzzy rough have emerged as a powerful vehicle deal with uncertain fuzzy in problems that involve very large number variables be analyzed short time. In order f...

A genemlized possibility-distribution-fuzzy-relationalmodel is proposed considering semantic ambiguity for membership attribute values and ambiguity contained in them. And then the extended relational algebra is shown. In order to eliminate the semantic ambiguity, a membership attribute is attached to each attribute. This clarifies the origin of membership attribute values. What a membership at...