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Bonding Grammars
We introduce bonding grammars, a graph grammar formalism developed to model DNA computation. It is a modification of fusion grammars introduced by...
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A general parsing algorithm with context matching for context-sensitive graph grammars
Context-sensitive graph grammars have been intuitive and rigorous formalisms for specifying visual programming languages, as they are sufficient...
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Schema Compliant Consistency Management via Triple Graph Grammars and Integer Linear Programming
In the field of Model-Driven Engineering, Triple Graph Grammars (TGGs) play an important role as a rule-based means of implementing consistency...
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Probabilistic grammars for modeling dynamical systems from coarse, noisy, and partial data
Ordinary differential equations (ODEs) are a widely used formalism for the mathematical modeling of dynamical systems, a task omnipresent in...
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Disambiguation Grammars for the Ukrainian Module
Grammatical ambiguity is one of the problems to be solved when preparing a morphosyntactic analyzer because when they are not solved, users have to...
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Discriminative estimation of probabilistic context-free grammars for mathematical expression recognition and retrieval
We present a discriminative learning algorithm for the probabilistic estimation of two-dimensional probabilistic context-free grammars (2D-PCFG) for...
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Ensuring User Interface Adaptation Consistency Through Triple Graph Grammars
As modern User Interfaces (UIs) are used in varying context-of-use situations, sophisticated mechanisms to control UI adaptations are needed. UI...
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Extending Abstract Categorial Grammars with Feature Structures: Theory and Practice
Abstract Categorial Grammars offer a versatile framework for modeling natural language syntax and semantics. However, they currently miss a key...
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Module Integration Using Graph Grammars (MIGRATE)
Software, whether desktop, mobile or web, is becoming more and more connected. Software development is also becoming more connected with ecosystems...
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Computing \(\textit{pre}^{*}\) for General Context Free Grammars
A systematic approach for addressing various problems related to context-free grammars involves employing the...
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Path Querying on Acyclic Graphs Using Boolean Grammars
AbstractGraph data models are widely employed in different areas of computer science, e.g., graph databases, bioinformatics, social network analysis,...
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Graph Rewriting for Graph Neural Networks
Given graphs as input, Graph Neural Networks (GNNs) support the inference of nodes, edges, attributes, or graph properties. Graph Rewriting...
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Pushdown Automata and Context-Free Grammars
In this chapter we study the class of pushdown automata and their relation to the class of context-free grammars and languages. We also consider...
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Avoiding unnecessary information loss: correct and efficient model synchronization based on triple graph grammars
Model synchronization, i.e., the task of restoring consistency between two interrelated models after a model change, is a challenging task. Triple...
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Classifying Sequences by Combining Context-Free Grammars and OWL Ontologies
This paper describes a pattern to formalise context-free grammars in OWL and its use for sequence classification. The proposed approach is compared...
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Dependency-enhanced graph convolutional networks for aspect-based sentiment analysis
Aspect-based sentiment analysis aims to extract aspect and opinion terms, and identify the sentiment polarities for such terms. The majority of...
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Finite Automata and Regular Grammars
In this chapter we introduce the notions of the deterministic finite automata and the nondeterministic finite automata, and we show their equivalence...
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HGAT: smart contract vulnerability detection method based on hierarchical graph attention network
With the widespread use of blockchain, more and more smart contracts are being deployed, and their internal logic is getting more and more...
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Linear Bounded Automata and Context-Sensitive Grammars
In this chapter we first show that the notions of the context-sensitive grammars and the type 1 grammars are equivalent. Then we show that every...