Related Research Articles
Natural language processing (NLP) is an interdisciplinary subfield of linguistics, computer science, and artificial intelligence concerned with the interactions between computers and human language, in particular how to program computers to process and analyze large amounts of natural language data. The goal is a computer capable of "understanding" the contents of documents, including the contextual nuances of the language within them. The technology can then accurately extract information and insights contained in the documents as well as categorize and organize the documents themselves.
Natural-language understanding (NLU) or natural-language interpretation (NLI) is a subtopic of natural-language processing in artificial intelligence that deals with machine reading comprehension. Natural-language understanding is considered an AI-hard problem.
Information extraction (IE) is the task of automatically extracting structured information from unstructured and/or semi-structured machine-readable documents and other electronically represented sources. In most of the cases this activity concerns processing human language texts by means of natural language processing (NLP). Recent activities in multimedia document processing like automatic annotation and content extraction out of images/audio/video/documents could be seen as information extraction
The Object Constraint Language (OCL) is a declarative language describing rules applying to Unified Modeling Language (UML) models developed at IBM and is now part of the UML standard. Initially, OCL was merely a formal specification language extension for UML. OCL may now be used with any Meta-Object Facility (MOF) Object Management Group (OMG) meta-model, including UML. The Object Constraint Language is a precise text language that provides constraint and object query expressions on any MOF model or meta-model that cannot otherwise be expressed by diagrammatic notation. OCL is a key component of the new OMG standard recommendation for transforming models, the Queries/Views/Transformations (QVT) specification.
Computer-aided software engineering (CASE) is the domain of software tools used to design and implement applications. CASE tools are similar to and were partly inspired by Computer-Aided Design (CAD) tools used for designing hardware products. CASE tools were used for developing high-quality, defect-free, and maintainable software. CASE software is often associated with methods for the development of information systems together with automated tools that can be used in the software development process.
UIMA, short for Unstructured Information Management Architecture, is an OASIS standard for content analytics, originally developed at IBM. It provides a component software architecture for the development, discovery, composition, and deployment of multi-modal analytics for the analysis of unstructured information and integration with search technologies.
Multilayered extended semantic networks (MultiNets) are both a knowledge representation paradigm and a language for meaning representation of natural language expressions that has been developed by Prof. Dr. Hermann Helbig on the basis of earlier Semantic Networks. It is used in a question-answering application for German called InSicht. It is also used to create a tutoring application developed by the university of University of Hagen to teach MultiNet to knowledge engineers.
Unstructured data is information that either does not have a pre-defined data model or is not organized in a pre-defined manner. Unstructured information is typically text-heavy, but may contain data such as dates, numbers, and facts as well. This results in irregularities and ambiguities that make it difficult to understand using traditional programs as compared to data stored in fielded form in databases or annotated in documents.
Biomedical text mining refers to the methods and study of how text mining may be applied to texts and literature of the biomedical and molecular biology domains. As a field of research, biomedical text mining incorporates ideas from natural language processing, bioinformatics, medical informatics and computational linguistics. The strategies developed through studies in this field are frequently applied to the biomedical and molecular biology literature available through services such as PubMed.
In linguistics, a treebank is a parsed text corpus that annotates syntactic or semantic sentence structure. The construction of parsed corpora in the early 1990s revolutionized computational linguistics, which benefitted from large-scale empirical data.
General Architecture for Text Engineering or GATE is a Java suite of tools originally developed at the University of Sheffield beginning in 1995 and now used worldwide by a wide community of scientists, companies, teachers and students for many natural language processing tasks, including information extraction in many languages.
The Ubiquitous Knowledge Processing Lab is a research lab at the Department of Computer Science at the Technische Universität Darmstadt. It was founded in 2006 by Iryna Gurevych.
Knowledge extraction is the creation of knowledge from structured and unstructured sources. The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing. Although it is methodically similar to information extraction (NLP) and ETL, the main criterion is that the extraction result goes beyond the creation of structured information or the transformation into a relational schema. It requires either the reuse of existing formal knowledge or the generation of a schema based on the source data.
Apache cTAKES: clinical Text Analysis and Knowledge Extraction System is an open-source Natural Language Processing (NLP) system that extracts clinical information from electronic health record unstructured text. It processes clinical notes, identifying types of clinical named entities — drugs, diseases/disorders, signs/symptoms, anatomical sites and procedures. Each named entity has attributes for the text span, the ontology mapping code, context, and negated/not negated.
The following outline is provided as an overview of and topical guide to natural-language processing:
Drama annotation is the process of annotating the metadata of a drama. Given a drama expressed in some medium, the process of metadata annotation identifies what are the elements that characterize the drama and annotates such elements in some metadata format. For example, in the sentence "Laertes and Polonius warn Ophelia to stay away from Hamlet." from the text Hamlet, the word "Laertes", which refers to a drama element, namely a character, will be annotated as "Char", taken from some set of metadata. This article addresses the drama annotation projects, with the sets of metadata and annotations proposed in the scientific literature, based markup languages and ontologies.
Iryna Gurevych is a German computer scientist. She is Professor at the Department of Computer Science of the Technical University of Darmstadt and Director of Ubiquitous Knowledge Processing Lab.
Bidirectional Encoder Representations from Transformers (BERT) is a family of masked-language models introduced in 2018 by researchers at Google. A 2020 literature survey concluded that "in a little over a year, BERT has become a ubiquitous baseline in Natural Language Processing (NLP) experiments counting over 150 research publications analyzing and improving the model."
References
- ↑ "alphaWorks Community". alphaworks.ibm.com. 20 October 2009.