Data Curation APIs
Understanding and analyzing big data is firmly recognized as a powerful and strategic priority. For deeper interpretation of and better intelligence with big data, it is important to transform raw data (unstructured, semi-structured and structured data sources, e.g., text, video, image data sets) into curated data: contextualized data and knowledge that is maintained and made available for use by end-users and applications. In particular, data curation acts as the glue between raw data and analytics, providing an abstraction layer that relieves users from time consuming, tedious and error prone curation tasks. In this context, the data curation process becomes a vital analytics asset for increasing added value and insights. In this paper, we identify and implement a set of curation APIs and make them available (on GitHub) to researchers and developers to assist them transforming their raw data into curated data. The curation APIs enable developers to easily add features - such as extracting keyword, part of speech, and named entities such as Persons, Locations, Organizations, Companies, Products, Diseases, Drugs, etc.; providing synonyms and stems for extracted information items leveraging lexical knowledge bases for the English language such as WordNet; linking extracted entities to external knowledge bases such as Google Knowledge Graph and Wikidata; discovering similarity among the extracted information items, such as calculating similarity between string, number, date and time data; classifying, sorting and categorizing data into various types, forms or any other distinct class; and indexing structured and unstructured data - into their applications.
Code (1)
Similar Papers 제목 키워드 기반
Augmented Understanding and Automated Adaptation of Curation Rules
Over the past years, there has been many efforts to curate and increase the added value of the raw data. Data curation has been defined as activities and processes an analyst undertakes to transform the raw data into con…
Entity Extraction using GANPOSLAPIS: Language Model-Augmented Police Investigation System
Crime situations are race against time. An AI-assisted criminal investigation system, providing prompt but precise legal counsel is in need for police officers. We introduce LAPIS (Language Model Augmented Police Investi…
Language ModelingLanguage ModellingLegal Reasoningmodel+1RustEvo^2: An Evolving Benchmark for API Evolution in LLM-based Rust Code Generation
Large Language Models (LLMs) have become pivotal tools for automating code generation in software development. However, these models face significant challenges in producing version-aware code for rapidly evolving langua…
Code GenerationNavigateRAGRetrieval-augmented GenerationLearning Therapist Policy from Therapist-Exoskeleton-Patient Interaction
Post-stroke rehabilitation is often necessary for patients to regain proper walking gait. However, the typical therapy process can be exhausting and physically demanding for therapists, potentially reducing therapy inten…
Leveraging Machine Learning to Detect Data Curation Activities
This paper describes a machine learning approach for annotating and analyzing data curation work logs at ICPSR, a large social sciences data archive. The systems we studied track curation work and coordinate team decisio…
BIG-bench Machine LearningDecision MakingManagement