39,323 research outputs found
RDF Knowledge Graph Visualization From a Knowledge Extraction System
In this paper, we present a system to visualize RDF knowledge graphs. These
graphs are obtained from a knowledge extraction system designed by
GEOLSemantics. This extraction is performed using natural language processing
and trigger detection. The user can visualize subgraphs by selecting some
ontology features like concepts or individuals. The system is also
multilingual, with the use of the annotated ontology in English, French, Arabic
and Chinese
DocTag2Vec: An Embedding Based Multi-label Learning Approach for Document Tagging
Tagging news articles or blog posts with relevant tags from a collection of
predefined ones is coined as document tagging in this work. Accurate tagging of
articles can benefit several downstream applications such as recommendation and
search. In this work, we propose a novel yet simple approach called DocTag2Vec
to accomplish this task. We substantially extend Word2Vec and Doc2Vec---two
popular models for learning distributed representation of words and documents.
In DocTag2Vec, we simultaneously learn the representation of words, documents,
and tags in a joint vector space during training, and employ the simple
-nearest neighbor search to predict tags for unseen documents. In contrast
to previous multi-label learning methods, DocTag2Vec directly deals with raw
text instead of provided feature vector, and in addition, enjoys advantages
like the learning of tag representation, and the ability of handling newly
created tags. To demonstrate the effectiveness of our approach, we conduct
experiments on several datasets and show promising results against
state-of-the-art methods.Comment: 10 page
brat: a Web-based Tool for NLP-Assisted Text Annotation
We introduce the brat rapid annotation tool (BRAT), an intuitive web-based tool for text annotation supported by Natural Language Processing (NLP) technology. BRAT has been developed for rich structured annotation for a variety of NLP tasks and aims to support manual curation efforts and increase annotator productivity using NLP techniques. We discuss several case studies of real-world annotation projects using pre-release versions of BRAT and present an evaluation of annotation assisted by semantic class disambiguation on a multicategory entity mention annotation task, showing a 15 % decrease in total annotation time. BRAT is available under an opensource license from
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