"Anglr is the 1st technology capable of analyzing texts without the need to know where the texts are about."
The technology is not limited to a specific language or language domain. Competitive technologies often need to be trained in specific contexts related to a specific application and need vocabularies or rule-sets to analyze data. So if you need to train the software where the data is about, then how to expect new insights?
The NewsAnglr app makes use of Anglr's self learning semantic technology to analyse online news feeds. Completely independent of any human action, NewsAnglr tracks thousands of online world-press sources analysing hundreds of thousands of articles a day. Within this news flood the app intelligently identifies the key messages and detects clusters and trends as they originate. In app users can consult this live analysis and find out what the key news topics are ranked by the number of sources that are writing about the topic.
NewsAnglr analyses hundreds of thousands of news articles a day. Articles are compared, topics extracted, clusters detected and key messages identified. Take a glimpse of newsAnglr's one day analysis of the online news flood.
NewsAnglr analyses and compares hundreds of thousands of articles from mainstream news sources, blogs, technology, financial news feeds, sport sites, science networks etc… It is a perfect showcase for Anglr’s flexibility towards multi language domains as well as its capability to do on the fly analysis, key concept detection and extraction, clustering and concept naming of big data sets of text.