Titlebook: Digital Libraries for Open Knowledge; 23rd International C Antoine Doucet,Antoine Isaac,Adam Jatowt Conference proceedings 2019 Springer Na

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Coner: A Collaborative Approach for Long-Tail Named Entity Recognition in Scientific Publications relevance of extracted entities into the training cycle of such iterative NER algorithms. This approach, called Coner, allows to still train new domain specific rare long-tail NER extractors with low costs, but with ever increasing performance while the algorithm is actively used in an application.

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: Quantifying the Impacts of Service to the Scientific Community work, toward this goal, we present a prototype digital library, ., that crawls, extracts, and quantifies the impacts of service based on one’s roles in the technical program committees of Computer Science conferences.

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Linking Semantic Fingerprints of Literature – from Simple Neural Embeddings Towards Contextualized P pharmaceutical entities can support the exploration of these associations and will help to assess and interpret predicted relationships. On the other hand, the prerequisite for building meaningful entity networks is an answer to the question: .-. In this paper, we investigate this question for impo

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Knowledge Graph Implementation of Archival Descriptions Through CIDOC-CRMsystem for document description and retrieval, to be used by professionals and the public. The early stages described here include the design of the core data model for archival records represented as the ArchOnto ontology and its embodiment in the ArchGraph knowledge graph. The goal of a semantic a

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Investigating Correlations of Inter-coder Agreement and Machine Annotation Performance for Historican performance and inter-annotator agreement are measured. In this context, information about training dataset size and agreement are used to predict average precision for concept classification. Finally, the impact of expert vs. non-expert annotations on person recognition is analyzed.

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Exploring Scholarly Data by Semantic Query on Knowledge Graph Embedding Spacedied word embedding space and use them to support data exploration. We also define the semantic queries, which are algebraic operations between the embedding vectors in the knowledge graph embedding space, to solve queries such as similarity and analogy between the entities on the original datasets.