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are represented as a knowledge graph based on Semantic Web ontologies, making them usable for further processes. As part of current research projects, the app will now be further developed for additional use cases
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of information retrieval, natural language processing, semantic technologies and human information interaction as foundation for innovative web portals and platforms for the search and use of research data. KTS
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Expertise in software development with Python, database and search engine technologies, machine learning frameworks, semantic web technologies, Docker Desired: expertise in working with scholarly data
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working is possible up to 2 days/week. Logic Mill platform Logic Mill is a scalable, open-access platform that identifies semantically similar scientific publications and patents, leveraging embeddings
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with researchers across the Institute to support data availability and storage through models, web databases, and scientific publications. Additionally, they will work closely with IT service units
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including diverse modelling approaches. They will collaborate with researchers across the Institute to support data availability and storage through models, web databases, and scientific publications
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representation languages such as RDF, OWL, SPARQL Experience with Semantic Web technologies, including graph databases (GraphDB, Neo4j), relevant libraries (RDFLib, owlready2) and other software (Protégé
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for students who would like to conduct research and work in the area of semantic analysis, search and recommendation of music data. The main areas of responsibility include the following: implementation/porting
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for students who would like to conduct research and work in the area of semantic analysis, search and recommendation of music data. The main areas of responsibility include the following: implementation/porting
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-related IT projects). Experience in software development in the environment of web-based applications (Java, JavaScript). Knowledge of semantic web/linked data technologies (RDF, SPARQL) and metadata