0000000000178647

AUTHOR

Paulis Barzdins

showing 4 related works from this author

Pini Language and PiniTree Ontology Editor: Annotation and Verbalisation for Atomised Journalism

2020

We present a new ontology language Pini and the PiniTree ontology editor supporting it. Despite Pini language bearing lot of similarities with RDF, UML class diagrams, Property Graphs and their frontends like Google Knowledge Graph and Protege, it is a more expressive language enabling FrameNet-style natural language annotation for Atomised journalism use case.

Computer science05 social sciences050801 communication & media studies02 engineering and technologycomputer.file_formatOntology languageProtégéLinguisticsAnnotation0508 media and communicationsUnified Modeling Language0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingJournalismClass diagramRDFcomputerNatural languagecomputer.programming_language
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Metamodel specialization based DSL for DL lifecycle data management

2020

A new Domain Specific Language (DSL) based approach to Deep Learning (DL) lifecycle data management (LDM) is presented: a very simple but universal DL LDM tool, still usable in practice (called Core tool); and an advanced extension mechanism, that converts the Core tool into a DSL tool building framework for DL LDM tasks. The method used is based on the metamodel specialisation approach for DSL modeling tools introduced by authors.

Domain-specific languageSIMPLE (military communications protocol)business.industryComputer scienceData managementDeep learning020207 software engineering02 engineering and technologyUSableMetamodelingDigital subscriber lineSoftware_SOFTWAREENGINEERINGSpecialization (logic)0202 electrical engineering electronic engineering information engineeringArtificial intelligencebusinessSoftware engineeringProceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedings
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Towards DSL for DL Lifecycle Data Management

2020

A new method based on Domain Specific Language (DSL) approach to Deep Learning (DL) lifecycle data management tool support is presented: a very simple DL lifecycle data management tool, which however is usable in practice (it will be called Core tool) and a very advanced extension mechanism which in fact converts the Core tool into domain specific tool (DSL tool) building framework for DL lifecycle data management tasks. The extension mechanism will be based on the metamodel specialization approach to DSL modeling tools introduced by authors. The main idea of metamodel specialization is that we, at first, define the Universal Metamodel (UMM) for a domain and then for each use case define a …

Domain-specific languagebusiness.industryComputer scienceData managementDeep learningUSableDomain (software engineering)MetamodelingDigital subscriber lineSoftware_SOFTWAREENGINEERINGSpecialization (functional)Artificial intelligencebusinessSoftware engineering
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RDF* Graph Database as Interlingua for the TextWorld Challenge

2019

This paper briefly describes the top-scoring submission to the First TextWorld Problems: A Reinforcement and Language Learning Challenge. To alleviate the partial observability problem, characteristic to the TextWorld games, we split the Agent into two independent components: Observer and Actor, communicating only via the Interlingua of the RDF* graph database. The RDF* graph database serves as the “world model” memory incrementally updated by the Observer via FrameNet informed Natural Language Understanding techniques and is used by the Actor for the efficient exploration and planning of the game Action sequences. We find that the deep-learning approach works best for the Observer componen…

InterlinguaInformation retrievalGraph databaseComputer scienceBacktrackingbusiness.industryDeep learningNatural language understandingcomputer.file_formatcomputer.software_genrelanguage.human_languagelanguageReinforcement learningArtificial intelligenceRDFFrameNetbusinesscomputer2019 IEEE Conference on Games (CoG)
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