The infamous Novel Corona-Virus (now officially named by W.H.O. as “COVID-19”) has been grabbing headlines the past few weeks. There is a lot of uncertainty as we don’t know the exact nature of the virus yet. We don’t know how long it will take for a vaccine to be found or whether it will disappear by itself just like SARS did.

As I went to the customer finance department, there is hardly any space to walk in. The table and corridor are full of paper. Is this a common scene in your department as well?

One of the biggest challenges that HR practitioners face today is finding the best people to recruit. In the past, this task has proven to be challenging, in part because of inefficient manual tasks that hamper the recruitment process and the lack of access to the right details. In fact, 46% of employers and workplace managers described “finding the right candidate” as the biggest obstacle to recruiting today, based on research undertaken by LinkedIn.

Cognitive document automation uses a variety of functions such as natural language processing (NLP) and machine learning for clustering, classification, isolation, OCR, extraction and (human language) interpretation of any kind of documents.

The huge amount of unstructured text data now accessible from both conventional and new media outlets, including social media, offers a rich source of information if the data can be organized. Named Entity Extraction provides a central function for knowledge building from half-structured and unstructured text sources.