Staffing 2.0 – Programmatic Matching 1/2

This blog post is the first in a series of two. Read the second blog post here. It probably already reached your attention but here at UnderstandLing we have been very active to make our self-invented term Programmatic Matching a thing. We are talking, of  course, about the staffing &…

Continue reading

Staffing 2.0 – Programmatic Matching 2/2

This blog post is the second in a series of two. Read the first blog post here. Automation – Programmatic Matching Using our personality extraction algorithm, we can gather the given personality of a candidate and the required personality of a role. Ideally we would do this on very generic…

Continue reading

Fake News Detection

With the recent developments of fake news playing a role in Trump’s elections, Cambridge Analytica using it to great manipulative extent and Mark Zuckerberg needing to testify on it against Congress, fake news is a hotter topic than ever. Fake news is basically nothing more than gossip, spread online. The…

Continue reading

Deriving Personality Traits from Text

If you’d ask me, one the most compelling fields in language processing is that of authorship profiling. In this field, we try to derive specific information about an (unknown) author of text based on what he or she writes alone, using a principle called stylometry. The idea is that what…

Continue reading

The (Non-)Sense of Word Vectors (2/2)

This is the second part in a two-series blog. Read the first part here. In the previous part, we discussed the differences between syntactical and semantical applications of natural language processing. In both scenarios, word vectors seem like a promising way forward given their recent popularity and success. As we…

Continue reading

The (Non-)Sense of Word Vectors (1/2)

In this series of two blogs, we will investigate the usage of word vectors for a variety of applications. It is no secret that we at UnderstandLing love Deep Learning and Word Vectors in particular. The implementation of word vectors that is FastText, even more so. We even have our…

Continue reading