Explore emerging trends in research data.
is an open source platform for live monitoring of innovation activity in
arXiv pre-prints, which are predominantly physical, computational and quantitative research disciplines.
Underpinning
is a data analysis and production system, which orchestrates a stable pipeline of data collection, enrichment and machine learning.
arXiv: a window on innovation.
arXiv is full of ground-breaking research, from the first report on the discovery of graphene, to seminal advances in AI research and the discovery of new building blocks of matter.
Hyperspecialist fields are hard to navigate.
Broad contextually relevant searches are hard to formulate, often requiring complex 'advanced' searches and expert-driven lists of keywords. 's arXlive Search search engine helps you see what you're missing by explicitly performing contextual searches, so that you don't get stuck searching for rare gems; whilst the Keyword Factory allows you to expand your technical vocabulary for making more expansive searches.
tools
arXlive Search: search for novel activity in arXiv articles, such as:
- Privacy and social media, from South American researchers, by novelty.
- The most recent, most novel research in the intersection of Cybersecurity and AI.
- Who was doing something like BERT before BERT was invented in 2018?
Keyword Factory: expand your technical vocabulary, for example relating to:
papers
In recent decades it has become the norm for entirely new industries to
arise in just a few years.
Traditional means of monitoring industrial and academic
activity are relatively slow, and this leads to laggy policy
decisions - which means
that the full benefits of these industries will not be distributed
evenly. As our team continue to publish academic outputs using
arXiv data we will integrate these into .
Deep learning, deep change
In the pipeline: Gender Diversity in AI (details)
Open source
All of our code is open source, and we only use open source data in the platform. Check out our
GitHub repo
to understand (or even contribute) the inner workings of . In addition to arXiv data, we also use open data from
GRID,
Microsoft Academic Graph and
DataHub.