Results 21 to 30 of about 802,028 (300)
Grammar-based genetic programming : a survey [PDF]
, 2010 Grammar formalisms are one of the key representation structures in Computer Science. So it is not surprising that they have also become important as a method for formalizing constraints in Genetic Programming (GP).
Whigham, P. A. (Peter A.) +5 more
core +1 more source
Applications of A Hyper–Graph Grammar System in Adaptive Finite–Element Computations
International Journal of Applied Mathematics and Computer Science, 2018 This paper describes application of a hyper-graph grammar system for modeling a three-dimensional adaptive finite element method. The hyper-graph grammar approach allows obtaining a linear computational cost of adaptive mesh transformations and ...
Gurgul Piotr +3 more
doaj +1 more source
Learning the Morphological and Syntactic Grammars for Named Entity Recognition
Information, 2022 In some languages, Named Entity Recognition (NER) is severely hindered by complex linguistic structures, such as inflection, that will confuse the data-driven models when perceiving the word’s actual meaning.
Mengtao Sun +4 more
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Graph design by graph grammar evolution [PDF]
2007 IEEE Congress on Evolutionary Computation, 2007 Determining the optimal topology of a graph is pertinent to many domains, as graphs can be used to model a variety of systems. Evolutionary algorithms constitute a popular optimization method, but scalability is a concern with larger graph designs. Generative representation schemes, often inspired by biological development, seek to address this by ...
Martin H. Luerssen, David M. W. Powers
openaire +2 more sources
Scientific Reports, 2022 We propose a deep graph learning approach for computing semantic textual similarity (STS) by using semantic role labels generated by a Semantic Role Labeling (SRL) system. SRL system output has significant challenges in dealing with graph-neural networks
Majid Mohebbi +2 more
doaj +1 more source
Parsing Graphs with Regular Graph Grammars [PDF]
Proceedings of the 6th Joint Conference on Lexical and Computational
Semantics (*SEM 2017), 2017 Recently, several datasets have become available which represent natural language phenomena as graphs. Hyperedge Replacement Languages (HRL) have been the focus of much attention as a formalism to represent the graphs in these datasets. Chiang et al.
Gilroy, Sorcha +2 more
openaire +3 more sources
CREATING AND MAINTAINING IFC–CITYGML CONVERSION RULES [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019 We employ a triple graph grammar to enable configurable conversion from IFC to CityGML. In this paper, we present the mathematical framework behind the graph transformation approach as well as an application to create, store and maintain transformation ...
H. Tauscher
doaj +1 more source
Problematic Unordered Queries in Temporal Moment Measurement by Using Natural Language
IEEE Access, 2023 This study examines the difficulty in measuring temporal moments by using natural language (TMMNL) in the untrimmed video. The purpose of TMMNL is to use natural language query to find a specific moment within a lengthy video.
Hafiza Sadia Nawaz, Junyu Dong
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Absence of phase transition in random language model
Physical Review Research, 2022 The random language model, proposed as a simple model of human languages, is defined by the averaged model of a probabilistic context-free grammar. This grammar expresses the process of sentence generation as a tree graph with nodes having symbols as ...
Kai Nakaishi, Koji Hukushima
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Engineering Grammar-Based Type Checking for Graph Rewriting Languages
IEEE Access, 2022 The ability to handle evolving graph structures is important both for programming languages and modeling languages. Of various languages that adopt graphs as primary data structures, a graph rewriting language LMNtal provides features of both (concurrent)
Naoki Yamamoto, Kazunori Ueda
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